Publications
2024
Comparison between Distance Functions for Approximate Bayesian Computation to Perform Stochastic Model Updating and Model Validation under Limited Data
Lye, A., Ferson, S., & Xiao, S. (2024). Comparison between Distance Functions for Approximate Bayesian Computation to Perform Stochastic Model Updating and Model Validation under Limited Data. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2). doi:10.1061/ajrua6.rueng-1223
Agent-based models under uncertainty.
Stepanov, V., & Ferson, S. (2024). Agent-based models under uncertainty.. F1000Research, 12, 834. doi:10.12688/f1000research.135249.3
Potential toxicity of iron ore tailings after the overflow of a mining dam in Nova Lima (Minas Gerais State, Brazil)
César, R. G., Migueles, C., Zanetti, P., Filgueira, L., Koifmann, G., Santos, D., . . . Ferson, S. (n.d.). Potential toxicity of iron ore tailings after the overflow of a mining dam in Nova Lima (Minas Gerais State, Brazil). Revista Brasileira de Geografia Física, 17(2), 1086-1097. doi:10.26848/rbgf.v17.2.p1086-1097
Older people's family relationships in disequilibrium during the COVID-19 pandemic. What really matters?
Derrer-Merk, E., Ferson, S., Mannis, A., Bentall, R., & Bennett, K. M. (2022). Older people's family relationships in disequilibrium during the COVID-19 pandemic. What really matters?. AGEING & SOCIETY. doi:10.1017/S0144686X22000435
How to Exploit What We Know About Input and Model: A Trans-probabilistic Approach to the 2022 AIAA UQ Challenge
Hristov, P. O., Ioannou, I., & Ferson, S. (2024). How to Exploit What We Know About Input and Model: A Trans-probabilistic Approach to the 2022 AIAA UQ Challenge. In AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2024-0944
Analysis of inspection records to evaluate the prevalence of ageing in the UK's industrial asset, base
Brown, C., Ferson, S., & Angelis, M. D. (2022). Analysis of inspection records to evaluate the prevalence of ageing in the UK's industrial asset, base. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 231-237). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-08-073-cd
Verified propagation of imprecise probabilities in non-linear ODEs
Gray, A., Forets, M., Schilling, C., Ferson, S., & Benet, L. (2024). Verified propagation of imprecise probabilities in non-linear ODEs. International Journal of Approximate Reasoning, 164, 109044. doi:10.1016/j.ijar.2023.109044
2023
Towards an automatic uncertainty compiler
Gray, N., de Angelis, M., & Ferson, S. (2023). Towards an automatic uncertainty compiler. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 160. doi:10.1016/j.ijar.2023.108951
Agent-based models under uncertainty
Stepanov, V., & Ferson, S. (n.d.). Agent-based models under uncertainty. F1000Research, 12, 834. doi:10.12688/f1000research.135249.1
Neural network model for imprecise regression with interval dependent variables.
Tretiak, K., Schollmeyer, G., & Ferson, S. (2023). Neural network model for imprecise regression with interval dependent variables.. Neural networks : the official journal of the International Neural Network Society, 161, 550-564. doi:10.1016/j.neunet.2023.02.005
Robust online updating of a digital twin with imprecise probability
de Angelis, M., Gray, A., Ferson, S., & Patelli, E. (2023). Robust online updating of a digital twin with imprecise probability. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 186. doi:10.1016/j.ymssp.2022.109877
Should data ever be thrown away? Pooling interval-censored data sets with different precision
Tretiak, K., & Ferson, S. (2023). Should data ever be thrown away? Pooling interval-censored data sets with different precision. International Journal of Approximate Reasoning. doi:10.1016/j.ijar.2023.02.007
Towards a Framework for Non-intrusive Uncertainty Propagation in the Preliminary Design of Aircraft Systems
Ioannou, I., Hristov, P. O., Yong, H. K., Marsh, R., Silva, E., Sobester, A., & Ferson, S. (2023). Towards a Framework for Non-intrusive Uncertainty Propagation in the Preliminary Design of Aircraft Systems. In AIAA SCITECH 2023 Forum. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2023-2373
Potential for Use of Iron Mining Tailings Calcined in a Flash Furnace as Pozzolanic Material
Gama, E. M. D., Brandão, P. R. G., Miranda, T. C., Seerig, T., & Ferson, S. (2023). Potential for Use of Iron Mining Tailings Calcined in a Flash Furnace as Pozzolanic Material. Geomaterials, 13(03), 35-50. doi:10.4236/gm.2023.133003
ROBUST PROBABILITY BOUNDS ANALYSIS FOR FAILURE ANALYSIS UNDER LACK OF DATA AND MODEL UNCERTAINTY
Lye, A., Gray, A., de Angelis, M., & Ferson, S. (2023). ROBUST PROBABILITY BOUNDS ANALYSIS FOR FAILURE ANALYSIS UNDER LACK OF DATA AND MODEL UNCERTAINTY. In Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp. 391-407). Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120223.10345.19797
2022
Bivariate dependency tracking in interval arithmetic
Gray, A., de Angelis, M., Patelli, E., & Ferson, S. (2023). Bivariate dependency tracking in interval arithmetic. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 186. doi:10.1016/j.ymssp.2022.109771
Belongingness challenged: Exploring the impact on older adults during the COVID-19 pandemic
Derrer-Merk, E., Ferson, S., Mannis, A., Bentall, R. P., & Bennett, K. M. (n.d.). Belongingness challenged: Exploring the impact on older adults during the COVID-19 pandemic. PLOS ONE, 17(10), e0276561. doi:10.1371/journal.pone.0276561
Is Protecting Older Adults from COVID-19 Ageism? A Comparative Cross-cultural Constructive Grounded Theory from the United Kingdom and Colombia
Derrer-Merk, E., Reyes-Rodriguez, M. -F., Salazar, A. -M., Guevara, M., Rodriguez, G., Fonseca, A. -M., . . . Bennett, K. M. (2022). Is Protecting Older Adults from COVID-19 Ageism? A Comparative Cross-cultural Constructive Grounded Theory from the United Kingdom and Colombia. JOURNAL OF SOCIAL ISSUES, 78(4), 900-923. doi:10.1111/josi.12538
Old dogs can learn new tricks. Loro viejo sí aprende a hablar. Evidence from the United Kingdom and Colombia.
Distribution-free risk analysis
Gray, A., Ferson, S., Kreinovich, V., & Patelli, E. (2022). Distribution-free risk analysis. International Journal of Approximate Reasoning, 146, 133-156. doi:10.1016/j.ijar.2022.04.001
Belongingness challenged: Exploring the impact on older adults during the COVID-19 pandemic.
How High Is High Enough? Assessing Financial Risk for Vertical Farms Using Imprecise Probability
Baumont de Oliveira, F. J., Ferson, S., Dyer, R. A. D., Thomas, J. M. H., Myers, P. D., & Gray, N. G. (2022). How High Is High Enough? Assessing Financial Risk for Vertical Farms Using Imprecise Probability. SUSTAINABILITY, 14(9). doi:10.3390/su14095676
Probability bounds analysis for Python
Gray, N., Ferson, S., De Angelis, M., Gray, A., & de Oliveira, F. B. (2022). Probability bounds analysis for Python. Software Impacts, 100246. doi:10.1016/j.simpa.2022.100246
Singhing with confidence: visualising the performance of confidence procedures
Wimbush, A., Gray, N., & Ferson, S. (2022). Singhing with confidence: visualising the performance of confidence procedures. Journal of Statistical Computation and Simulation, 1-17. doi:10.1080/00949655.2022.2044814
Correlated Boolean Operators for Uncertainty Logic
Miralles-Dolz, E., Gray, A., Patelli, E., & Ferson, S. (2022). Correlated Boolean Operators for Uncertainty Logic. In Communications in Computer and Information Science (pp. 798-811). Springer International Publishing. doi:10.1007/978-3-031-08971-8_64
2021
While, In General, Uncertainty Quantification (UQ) Is NP-Hard, Many Practical UQ Problems Can Be Made Feasible
Gray, A., Ferson, S., Kosheleva, O., & Kreinovich, V. (2021). While, In General, Uncertainty Quantification (UQ) Is NP-Hard, Many Practical UQ Problems Can Be Made Feasible. In 2021 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2021). doi:10.1109/SSCI50451.2021.9659990
Constructing consonant beliefs from multivariate data with scenario theory
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing consonant beliefs from multivariate data with scenario theory. Virtually from Liverpool.
Constructing consonant beliefs from multivariate data with scenario theory
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing consonant beliefs from multivariate data with scenario theory. Poster session presented at the meeting of The International Symposium on Imprecise Probabilities: Theories and Applications.
Beyond probabilities: A possibilistic framework to interpret ensemble predictions and fuse imperfect sources of information
Le Carrer, N., & Ferson, S. (2021). Beyond probabilities: A possibilistic framework to interpret ensemble predictions and fuse imperfect sources of information. QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, 147(739), 3410-3433. doi:10.1002/qj.4135
Response to the comment Confidence in confidence distributions!
Martin, R., Balch, M. S., & Ferson, S. (2021). Response to the comment Confidence in confidence distributions!. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 477(2250). doi:10.1098/rspa.2020.0579
Constructing Consonant Predictive Beliefs from Data with Scenario Theory
De Angelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing Consonant Predictive Beliefs from Data with Scenario Theory. In Proceedings of Machine Learning Research Vol. 147 (pp. 362). Granada, Spain.
Distribution-free uncertainty propagation
Ferson, S., & Gray, A. (2021, May 17). Distribution-free uncertainty propagation. In 9th International Workshop on Reliable Engineering Computing (REC2021). Virtual (Taormina, Italy).
What’s Z−X, when Z = X+Y? Dependency tracking in interval arithmetic with bivariate sets
Gray, A., De Angelis, M., Ferson, S., & Patelli, E. (2021, May 17). What’s Z−X, when Z = X+Y? Dependency tracking in interval arithmetic with bivariate sets. In 9th International Workshop on Reliable Engineering Computing (REC2021). Virtual (Taormina, Italy).
Transformation of measurement uncertainties into low-dimensional feature vector space
Alexiadis, A., Ferson, S., & Patterson, E. A. (2021). Transformation of measurement uncertainties into low-dimensional feature vector space. ROYAL SOCIETY OPEN SCIENCE, 8(3). doi:10.1098/rsos.201086
Is no test better than a bad test: Impact of diagnostic uncertainty on the spread of COVID-19 (vol 15, e0240775, 2020)
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De Angelis, M., . . . Ferson, S. (2021). Is no test better than a bad test: Impact of diagnostic uncertainty on the spread of COVID-19 (vol 15, e0240775, 2020). PLOS ONE, 16(2). doi:10.1371/journal.pone.0247129
A Collaborative Decision Support System Framework for Vertical Farming Business Developments
De Oliveira, F. J. B., Ferson, S., & Dyer, R. (2021). A Collaborative Decision Support System Framework for Vertical Farming Business Developments. INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY, 13(1), 34-66. doi:10.4018/IJDSST.2021010103
Constructing Consonant Predictive Beliefs from Data with Scenario Theory
DeAngelis, M., Rocchetta, R., Gray, A., & Ferson, S. (2021). Constructing Consonant Predictive Beliefs from Data with Scenario Theory. In PROCEEDINGS OF THE TWELVETH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS Vol. 147 (pp. 357-360). Retrieved from https://www.webofscience.com/
Dependent Possibilistic Arithmetic Using Copulas
Gray, A., Hose, D., De Angelis, M., Hanss, M., & Ferson, S. (2021). Dependent Possibilistic Arithmetic Using Copulas. In PROCEEDINGS OF THE TWELVETH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS Vol. 147 (pp. 169-179). Retrieved from https://www.webofscience.com/
Handling the Uncertainty with Confidence in Human Reliability Analysis
Morais, C., Ferson, S., Moura, R., Tolo, S., Beer, M., & Patelli, E. (2021). Handling the Uncertainty with Confidence in Human Reliability Analysis. In Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021) (pp. 3312-3318). Research Publishing Services. doi:10.3850/978-981-18-2016-8_575-cd
2020
Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis
Oparaji, B. U., Clearkin, L., Ferson, S., De Angelis, M., Ferrer-Fernandez, M., Calleja, D., . . . Derrer-Merk, E. (2020). Comment on: British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis. RHEUMATOLOGY, 59(12), E159. doi:10.1093/rheumatology/keaa265
Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De Angelis, M., . . . Ferson, S. (2020). Is "No test is better than a bad test"? Impact of diagnostic uncertainty in mass testing on the spread of Covid-19. PLoS One. doi:10.1371/journal.pone.0240775
Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19
Gray, N., Calleja, D., Wimbush, A., Miralles-Dolz, E., Gray, A., De-Angelis, M., . . . Ferson, S. (2020). Is “no test is better than a bad test”? Impact of diagnostic uncertainty in mass testing on the spread of COVID-19. doi:10.1101/2020.04.16.20067884
Optimising cargo loading and ship scheduling in tidal areas
Le Carrer, N., Ferson, S., & Green, P. L. (2020). Optimising cargo loading and ship scheduling in tidal areas. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 280(3), 1082-1094. doi:10.1016/j.ejor.2019.08.002
A Possibilistic Interpretation of Ensemble Predictions: Application to Shipping Optimization in Tidal Areas
Carrer, N. L., & Ferson, S. (2020). A Possibilistic Interpretation of Ensemble Predictions: Application to Shipping Optimization in Tidal Areas. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (pp. 4953). Research Publishing Services. doi:10.3850/978-981-14-8593-0_4543-cd
A Problem in the Bayesian Analysis of Data without Gold Standards
Gray, N., Angelis, M. D., Calleja, D., & Ferson, S. (2019). A Problem in the Bayesian Analysis of Data without Gold Standards. In Proceedings of the 29th European Safety and Reliability Conference (ESREL) (pp. 2628-2634). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0458-cd
Prediction And Decision Making From Bad Data
Ferson, S. (2019). Prediction And Decision Making From Bad Data. In Proceedings of the 29th European Safety and Reliability Conference (ESREL) (pp. 29). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0005-cd
2019
On the dimensionality of inference in credal nets with interval probabilities
De Angelis, M., Estrada Lugo, H. D., Patelli, E., & Ferson, S. (2019). On the dimensionality of inference in credal nets with interval probabilities. Poster session presented at the meeting of ISIPTA 2019. Ghent.
Coverage Probability Fails to Ensure Reliable Inference
Balch, M., Martin, R., & Ferson, S. (2019). Coverage Probability Fails to Ensure Reliable Inference. Proceedings of the Royal Society of London. Mathematical, Physical and Engineering Sciences.
BLACK-BOX PROPAGATION OF FAILURE PROBABILITIES UNDER EPISTEMIC UNCERTAINTY
De Angelis, M., Ferson, S., Patelli, E., & Kreinovich, V. (2019). BLACK-BOX PROPAGATION OF FAILURE PROBABILITIES UNDER EPISTEMIC UNCERTAINTY. In Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp. 713-723). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6373.18699
COMPUTING WITH UNCERTAINTY: INTRODUCING PUFFIN THE AUTOMATIC UNCERTAINTY COMPILER
Gray, N., De Angelis, M., & Ferson, S. (2019). COMPUTING WITH UNCERTAINTY: INTRODUCING PUFFIN THE AUTOMATIC UNCERTAINTY COMPILER. In Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp. 487-497). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120219.6354.18702
2018
Quantification of Incertitude in Black Box Simulation Codes
Calder, A. C., Hoffman, M. M., Willcox, D. E., Katz, M. P., Swesty, F. D., & Ferson, S. (2018). Quantification of Incertitude in Black Box Simulation Codes. In 12TH INTERNATIONAL CONFERENCE ON NUMERICAL MODELING OF SPACE PLASMA FLOWS: ASTRONUM-2017 Vol. 1031. doi:10.1088/1742-6596/1031/1/012016
Comparative, collaborative, and integrative risk governance for emerging technologies
Linkov, I., Trump, B. D., Anklam, E., Berube, D., Boisseasu, P., Cummings, C., . . . Vermeire, T. (2018). Comparative, collaborative, and integrative risk governance for emerging technologies.. Environment systems & decisions, 38(2), 170-176. doi:10.1007/s10669-018-9686-5
2017
Satellite conjunction analysis and the false confidence theorem
2016
Ecological modeling in risk assessment: Chemical effects on populations, ecosystems, and landscapes
Pastorok, R. A., Bartell, S. M., Ferson, S., & Ginzburg, L. R. (2016). Ecological modeling in risk assessment: Chemical effects on populations, ecosystems, and landscapes.
Population models - scalar abundance
Ferson, S. (2016). Population models - scalar abundance. In Ecological Modeling in Risk Assessment: Chemical Effects on Populations, Ecosystems, and Landscapes (pp. 37-53).
Ecological Risk Assessment for Mink and Short-Tailed Shrew Exposed to PCBs, Dioxins, and Furans in the Housatonic River Area
Moore, D. R. J., Breton, R. L., DeLong, T. R., Ferson, S., Lortie, J. P., MacDonald, D. B., . . . Aslund, M. W. (2016). Ecological Risk Assessment for Mink and Short-Tailed Shrew Exposed to PCBs, Dioxins, and Furans in the Housatonic River Area. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT, 12(1), 174-184. doi:10.1002/ieam.1661
2015
Accounting for uncertainty in DNA sequencing data
O Rawe, J., Ferson, S., & Lyon, G. (2015). Accounting for uncertainty in DNA sequencing data. Trends in Genetics, 31(2), 61-66. doi:10.1016/j.tig.2014.12.002
Natural language of uncertainty: Numeric hedge words
Ferson, S., O Rawe, J., Antonenko, A., Siegrist, J., Mickley, J., C Luhmann, C., . . . Finkel, A. (2015). Natural language of uncertainty: Numeric hedge words. International Journal of Approximate Reasoning, 57, 19-39. doi:10.1016/j.ijar.2014.11.003
2014
Computing with Confidence: Imprecise Posteriors and Predictive Distributions
Ferson, S., O'Rawe, J., & Balch, M. (2014). Computing with Confidence: Imprecise Posteriors and Predictive Distributions. In Vulnerability, Uncertainty, and Risk (pp. 895-904). American Society of Civil Engineers. doi:10.1061/9780784413609.091
2013
Data Anonymization that Leads to the Most Accurate Estimates of Statistical Characteristics: Fuzzy-Motivated Approach
Xiang, G., Ferson, S., Ginzburg, L., Longpre, L., Mayorga, E., & Kosheleva, O. (2013). Data Anonymization that Leads to the Most Accurate Estimates of Statistical Characteristics: Fuzzy-Motivated Approach. In PROCEEDINGS OF THE 2013 JOINT IFSA WORLD CONGRESS AND NAFIPS ANNUAL MEETING (IFSA/NAFIPS) (pp. 611-616). Retrieved from https://www.webofscience.com/
The Relationship Between Mindful Parenting and Distress in Parents of Children with an Autism Spectrum Disorder
Beer, M., Ward, L., & Moar, K. (2013). The Relationship Between Mindful Parenting and Distress in Parents of Children with an Autism Spectrum Disorder. MINDFULNESS, 4(2), 102-112. doi:10.1007/s12671-012-0192-4
Imprecise probabilities in engineering analyses
Beer, M., Ferson, S., & Kreinovich, V. (2013). Imprecise probabilities in engineering analyses. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 4-29. doi:10.1016/j.ymssp.2013.01.024
Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword
Beer, M., & Ferson, S. (2013). Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 1-3. doi:10.1016/j.ymssp.2013.03.018
Computing with confidence
Ferson, S., Balch, M., Sentz, K., & Siegrist, J. (2013). Computing with confidence. In ISIPTA 2013 - Proceedings of the 8th International Symposium on Imprecise Probability: Theories and Applications (pp. 129-138).
2012
Commentary: IUCN classifications under uncertainty
Akcakaya, H. R., Ferson, S., Burgman, M. A., Keith, D. A., Mace, G. M., & Todd, C. R. (2012). Commentary: IUCN classifications under uncertainty. ENVIRONMENTAL MODELLING & SOFTWARE, 38, 119-121. doi:10.1016/j.envsoft.2012.05.009
Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Computational Implementation
Helton, J. C., & Sallaberry, C. J. (2012). Uncertainty and Sensitivity Analysis: From Regulatory Requirements to Conceptual Structure and Computational Implementation. In Unknown Conference (pp. 60-77). Springer Berlin Heidelberg. doi:10.1007/978-3-642-32677-6_5
Discussion
Ferson, S., Helton, J., Kahan, W., Pascual, P., Goldstein, M., & O'Hagan, A. (2012). Discussion. In IFIP Advances in Information and Communication Technology Vol. 377 AICT (pp. 117-122). doi:10.1007/978-3-642-32677-6_7
Verified Computation with Probabilities
Ferson, S., & Siegrist, J. (2012). Verified Computation with Probabilities. In Unknown Conference (pp. 95-122). Springer Berlin Heidelberg. doi:10.1007/978-3-642-32677-6_7
2011
Structural Reliability Assessment with Fuzzy Probabilities
Beer, M., Zhang, M., Tong, Q. S., & Ferson, S. (2011). Structural Reliability Assessment with Fuzzy Probabilities. In ISIPTA '11 - PROCEEDINGS OF THE SEVENTH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS (pp. 61-70). Retrieved from https://www.webofscience.com/
Probabilistic bounding analysis in the Quantification of Margins and Uncertainties
Sentz, K., & Ferson, S. (2011). Probabilistic bounding analysis in the Quantification of Margins and Uncertainties. RELIABILITY ENGINEERING & SYSTEM SAFETY, 96(9), 1126-1136. doi:10.1016/j.ress.2011.02.014
Fuzzy Probability in Engineering Analyses
Beer, M., & Ferson, S. (2011). Fuzzy Probability in Engineering Analyses. In Vulnerability, Uncertainty, and Risk (pp. 53-61). American Society of Civil Engineers. doi:10.1061/41170(400)7
Statistic Inference under Two Structurally Different Approaches to Interval Data
Ferson, S., & Siegrist, J. (2011). Statistic Inference under Two Structurally Different Approaches to Interval Data. In Vulnerability, Uncertainty, and Risk (pp. 29-36). American Society of Civil Engineers. doi:10.1061/41170(400)4
Statistically Detecting Clustering for Rare Events
Siegrist, J., Ferson, S., Goode, J., & Grimson, R. (2011). Statistically Detecting Clustering for Rare Events. In Vulnerability, Uncertainty, and Risk (pp. 526-532). American Society of Civil Engineers. doi:10.1061/41170(400)64
Uncertainty Arithmetic on Excel Spreadsheets: Add-In for Intervals, Probability Distributions, and Probability Boxes
Ferson, S., Mickley, J., & McGill, W. (2011). Uncertainty Arithmetic on Excel Spreadsheets: Add-In for Intervals, Probability Distributions, and Probability Boxes. In Vulnerability, Uncertainty, and Risk (pp. 70-77). American Society of Civil Engineers. doi:10.1061/41170(400)9
Probability Bounds Analysis for Nonlinear Dynamic Process Models
Enszer, J. A., Lin, Y., Ferson, S., Corliss, G. F., & Stadtherr, M. A. (2011). Probability Bounds Analysis for Nonlinear Dynamic Process Models. AICHE JOURNAL, 57(2), 404-422. doi:10.1002/aic.12278
2010
Bounding Uncertainty Analyses
Ferson, S., Moore, D., Van den Brink, P., Estes, T., Gallagher, K., O’Connor, R., & Verdonck, F. (2010). Bounding Uncertainty Analyses. In Application of Uncertainty Analysis to Ecological Risks of Pesticides (pp. 89-122). CRC Press. doi:10.1201/ebk1439807347-c6
How to detect and avoid pitfalls, traps, and swindles
Joermann, G., La Point, T. W., Burns, L. A., Carbone, J. P., Delorme, P. D., Ferson, S., . . . Traas, T. P. (2010). How to detect and avoid pitfalls, traps, and swindles. In Application of Uncertainty Analysis to Ecological Risks of Pesticides (pp. 155-163).
Introduction and objectives
Hart, A., Farrar, D., Urban, D., Fischer, D., Point, T. L., Romijn, K., & Ferson, S. (2010). Introduction and objectives. In Application of Uncertainty Analysis to Ecological Risks of Pesticides (pp. 1-10).
Problem formulation for probabilistic ecological risk assessments
Hart, A., Ferson, S., Shaw, J., Suter, G. W., Chapman, P. F., de Fur, P. L., . . . Jones, P. D. (2010). Problem formulation for probabilistic ecological risk assessments. In Application of Uncertainty Analysis to Ecological Risks of Pesticides (pp. 11-30).
2009
Trade-off between sample size and accuracy: Case of measurements under interval uncertainty
Nguyen, H. T., Kosheleva, O., Kreinovich, V., & Ferson, S. (2009). Trade-off between sample size and accuracy: Case of measurements under interval uncertainty. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 50(8), 1164-1176. doi:10.1016/j.ijar.2009.06.013
Validation of imprecise probability models
Ferson, S., & Oberkampf, W. L. (2009). Validation of imprecise probability models. International Journal of Reliability and Safety, 3(1/2/3), 3. doi:10.1504/ijrs.2009.026832
2008
Trade-off between sample size and accuracy: Case of dynamic measurements under interval uncertainty
Nguyen, H. T., Kosheleva, O., Kreinovich, V., & Ferson, S. (2008). Trade-off between sample size and accuracy: Case of dynamic measurements under interval uncertainty. In INTERVAL / PROBABILISTIC UNCERTAINTY AND NON-CLASSICAL LOGICS Vol. 46 (pp. 45-+). Retrieved from https://www.webofscience.com/
How to measure a degree of mismatch between probability models, p-boxes, etc.:: A decision-theory-motivated utility-based approach
Longpre, L., Ferson, S., & Tucker, W. T. (2008). How to measure a degree of mismatch between probability models, p-boxes, etc.:: A decision-theory-motivated utility-based approach. In 2008 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1 AND 2 (pp. 540-545). Retrieved from https://www.webofscience.com/
Probability boxes as info-gap models
Ferson, S., & Tucker, W. T. (2008). Probability boxes as info-gap models. In 2008 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1 AND 2 (pp. 625-630). Retrieved from https://www.webofscience.com/
Model validation and predictive capability for the thermal challenge problem
Ferson, S., Oberkampf, W. L., & Ginzburg, L. (2008). Model validation and predictive capability for the thermal challenge problem. In COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING Vol. 197 (pp. 2408-2430). doi:10.1016/j.cma.2007.07.030
Population-Level Effects of PCBs on Wood Frogs (<i>Rana sylvatica</i>) Breeding in Vernal Pools Associated with the Housatonic River, Pittsfi eld to Lenoxdale, Massachusetts,
Tucker, W. T., Litzgus, J. D., Ferson, S., AkçAkaya, H. R., Thompson, M. E., Fortm, D. J., & Lortie, J. P. (2008). Population-Level Effects of PCBs on Wood Frogs (<i>Rana sylvatica</i>) Breeding in Vernal Pools Associated with the Housatonic River, Pittsfi eld to Lenoxdale, Massachusetts,. In Demographic Toxicity (pp. 97-122). Oxford University PressNew York, NY. doi:10.1093/oso/9780195332964.003.0007
A frequency/consequence-based technique for visualizing and communicating uncertainty and perception of risk
Siavin, D., Tucker, W. T., & Ferson, S. (2008). A frequency/consequence-based technique for visualizing and communicating uncertainty and perception of risk. In STRATEGIES FOR RISK COMMUNICATION: EVOLUTION, EVIDENCE, EXPERIENCE Vol. 1128 (pp. 63-77). doi:10.1196/annals.1399.008
Evolved altruism, strong reciprocity, and perception of risk
Tucker, W. T., & Ferson, S. (2008). Evolved altruism, strong reciprocity, and perception of risk. In STRATEGIES FOR RISK COMMUNICATION: EVOLUTION, EVIDENCE, EXPERIENCE Vol. 1128 (pp. 111-120). doi:10.1196/annals.1399.012
Strategies for risk communication - Evolution, evidence, experience
Tucker, W. T., & Ferson, S. (2008). Strategies for risk communication - Evolution, evidence, experience. In STRATEGIES FOR RISK COMMUNICATION: EVOLUTION, EVIDENCE, EXPERIENCE Vol. 1128 (pp. IX-XII). doi:10.1196/annals.1399.000
Trade-off between sample size and accuracy: Case of static measurements under interval uncertainty
Nguyen, H. T., & Kreinovich, V. (2008). Trade-off between sample size and accuracy: Case of static measurements under interval uncertainty. In INTERVAL / PROBABILISTIC UNCERTAINTY AND NON-CLASSICAL LOGICS Vol. 46 (pp. 32-+). Retrieved from https://www.webofscience.com/
2007
Fitting a normal distribution to interval and fuzzy data
Xiang, G., Kreinovich, V., & Ferson, S. (2007). Fitting a normal distribution to interval and fuzzy data. In NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY (pp. 560-+). doi:10.1109/NAFIPS.2007.383901
Interval versions of statistical techniques with applications to environmental analysis, bioinformatics, and privacy in statistical databases
Kreinovich, V., Longpre, L., Starks, S. A., Xiang, G., Beck, J., Kandathi, R., . . . Hajagos, J. (2007). Interval versions of statistical techniques with applications to environmental analysis, bioinformatics, and privacy in statistical databases. In JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS Vol. 199 (pp. 418-423). doi:10.1016/j.cam.2005.07.041
2006
Sensitivity analysis using probability bounding
Ferson, S., & Tucker, W. T. (2006). Sensitivity analysis using probability bounding. RELIABILITY ENGINEERING & SYSTEM SAFETY, 91(10-11), 1435-1442. doi:10.1016/j.ress.2005.11.052
Varying correlation coefficients can underestimate uncertainty in probabilistic models
Ferson, S., & Hajagos, J. G. (2006). Varying correlation coefficients can underestimate uncertainty in probabilistic models. In RELIABILITY ENGINEERING & SYSTEM SAFETY Vol. 91 (pp. 1461-1467). doi:10.1016/j.ress.2005.11.043
Computing mean and variance under Dempster-Shafer uncertainty: Towards faster algorithms
Kreinovich, V., Xiang, G., & Ferson, S. (2006). Computing mean and variance under Dempster-Shafer uncertainty: Towards faster algorithms. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 42(3), 212-227. doi:10.1016/j.ijar.2005.12.001
Computing best-possible bounds for the distribution of a sum of several variables is NP-hard
Kreinovich, V., & Ferson, S. (2006). Computing best-possible bounds for the distribution of a sum of several variables is NP-hard. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 41(3), 331-342. doi:10.1016/j.ijar.2005.06.009
Adding Constraints to Situations When, In Addition to Intervals,We Also Have Partial Information about Probabilities
Ceberio, M., Kreinovich, V., Xiang, G., Ferson, S., & Joslyn, C. (2006). Adding Constraints to Situations When, In Addition to Intervals,We Also Have Partial Information about Probabilities. In 12th GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics (SCAN 2006) (pp. 30). IEEE. doi:10.1109/scan.2006.7
2005
How the concept of information as average number of "yes"-"no" questions (bits) can be extended to intervals, p-boxes, and more general uncertainty
Kreinovich, V., Xiang, G., & Ferson, S. (2005). How the concept of information as average number of "yes"-"no" questions (bits) can be extended to intervals, p-boxes, and more general uncertainty. In NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society (pp. 80-85). doi:10.1109/NAFIPS.2005.1548512
Case study part 1: How to calculate appropriate deterministic long-term toxicity to exposure ratios (TERs) for birds and mammals
Shore, R. F., Crocker, D. R., Akcakaya, H. R., Bennett, R. S., Chapman, P. F., Clook, M., . . . Topping, C. (2005). Case study part 1: How to calculate appropriate deterministic long-term toxicity to exposure ratios (TERs) for birds and mammals. ECOTOXICOLOGY, 14(8), 877-893. doi:10.1007/s10646-005-0034-4
Case study part 2: Probabitistic modelling of long-term effects of pesticides on individual breeding success in birds and mammals
Roelofs, W., Crocker, D. R., Shore, R. F., Moore, D. R. J., Smith, G. C., Akcakaya, H. R., . . . Topping, C. (2005). Case study part 2: Probabitistic modelling of long-term effects of pesticides on individual breeding success in birds and mammals. ECOTOXICOLOGY, 14(8), 895-923. doi:10.1007/s10646-005-0035-3
Exact Bounds on Finite Populations of Interval Data
Ferson, S., Ginzburg, L., Kreinovich, V., Longpré, L., & Aviles, M. (2005). Exact Bounds on Finite Populations of Interval Data. Reliable Computing, 11(3), 207-233. doi:10.1007/s11155-005-3616-1
Outlier Detection under Interval Uncertainty: Algorithmic Solvability and Computational Complexity
Kreinovich, V., Longpr�, L., Patangay, P., Ferson, S., & Ginzburg, L. (2005). Outlier Detection under Interval Uncertainty: Algorithmic Solvability and Computational Complexity. Reliable Computing, 11(1), 59-76. doi:10.1007/s11155-005-5943-7
2004
A feasible algorithm for locating concave and convex zones of interval data and its use in statistics-based clustering
Kreinovich, V., Pauwels, E. J., Ferson, S. A., & Ginzburg, L. (2004). A feasible algorithm for locating concave and convex zones of interval data and its use in statistics-based clustering. NUMERICAL ALGORITHMS, 37(1-4), 225-232. doi:10.1023/B:NUMA.0000049469.02043.24
A new Cauchy-based black-box technique for uncertainty in risk analysis
Kreinovich, V., & Ferson, S. A. (2004). A new Cauchy-based black-box technique for uncertainty in risk analysis. RELIABILITY ENGINEERING & SYSTEM SAFETY, 85(1-3), 267-279. doi:10.1016/j.ress.2004.03.016
Arithmetic with uncertain numbers: rigorous and (often) best possible answers
Ferson, S., & Hajagos, J. G. (2004). Arithmetic with uncertain numbers: rigorous and (often) best possible answers. RELIABILITY ENGINEERING & SYSTEM SAFETY, 85(1-3), 135-152. doi:10.1016/j.ress.2004.03.008
Challenge problems: uncertainty in system response given uncertain parameters
Oberkampf, W. L., Helton, J. C., Joslyn, C. A., Wojtkiewicz, S. F., & Ferson, S. (2004). Challenge problems: uncertainty in system response given uncertain parameters. RELIABILITY ENGINEERING & SYSTEM SAFETY, 85(1-3), 11-19. doi:10.1016/j.ress.2004.03.002
Summary from the epistemic uncertainty workshop: consensus amid diversity
Ferson, S., Joslyn, C. A., Helton, J. C., Oberkampf, W. L., & Sentz, K. (2004). Summary from the epistemic uncertainty workshop: consensus amid diversity. RELIABILITY ENGINEERING & SYSTEM SAFETY, 85(1-3), 355-369. doi:10.1016/j.ress.2004.03.023
Equivalence of methods for uncertainty propagation of real-valued random variables
Regan, H. M., Ferson, S., & Berleant, D. (2004). Equivalence of methods for uncertainty propagation of real-valued random variables. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 36(1), 1-30. doi:10.1016/j.ijar.2003.07.013
Probabilities, intervals, what next? extension of interval computations to situations with partial information about probabilities
Krenovich, V., Solopchenko, G. N., Ferson, S. A., Ginzburg, L., & Aló, R. (2004). Probabilities, intervals, what next? extension of interval computations to situations with partial information about probabilities. In 10th IMEKO TC7 Symposium on Advances of Measurement Science 2004 (pp. 130-135).
2003
Berleant, D., Cheong, M. -P., Chu, C., Guan, Y., Kamal, A., Shedblé, G., . . . Peters, J. F. (2003). Unknown Title. Reliable Computing, 9(6), 407-418. doi:10.1023/a:1025888503247
Kreinovich, V., Ferson, S., & Ginzburg, L. (2003). Unknown Title. Reliable Computing, 9(6), 441-463. doi:10.1023/a:1025841220835
Reliability of risk analyses for contaminated groundwater
Ferson, S., & Tucker, W. T. (2003). Reliability of risk analyses for contaminated groundwater. In GROUNDWATER QUALITY MODELING AND MANAGEMENT UNDER UNCERTAINTY (pp. 226-235). Retrieved from https://www.webofscience.com/
Setting cleanup targets in a probabilistic assessment
Tucker, W. T., Myers, D. S., & Ferson, S. (2003). Setting cleanup targets in a probabilistic assessment. In GROUNDWATER QUALITY MODELING AND MANAGEMENT UNDER UNCERTAINTY (pp. 23-33). Retrieved from https://www.webofscience.com/
Detecting and explaining rare event-clusters in sparse data sets: Some initial results
Ricci, P. F., & Ferson, S. (2003). Detecting and explaining rare event-clusters in sparse data sets: Some initial results. Technology: Journal of the Franklin Institute, 9(1-2), 85-94.
Outlier detection under interval and fuzzy uncertainty:: Algorithmic solvability and computational complexity
Kreinovich, V., Patangay, P., Longpré, L., Starks, S. A., Campos, C., Ferson, S., & Ginzburg, L. (2003). Outlier detection under interval and fuzzy uncertainty:: Algorithmic solvability and computational complexity. In NAFIPS'2003: 22ND INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS PROCEEDINGS (pp. 401-406). Retrieved from https://www.webofscience.com/
Outlier detection under interval uncertainty:: Algorithmic solvability and computational complexity
Kreinovich, V., Longpré, L., Patangay, P., Ferson, S., & Ginzburg, L. (2003). Outlier detection under interval uncertainty:: Algorithmic solvability and computational complexity. In LARGE-SCALE SCIENTIFIC COMPUTING Vol. 2907 (pp. 238-245). Retrieved from https://www.webofscience.com/
Realism and relevance of ecological models used in chemical risk assessment
Bartell, S. M., Pastorok, R. A., Akçakaya, H. R., Regan, H., Ferson, S., & Mackay, C. (2003). Realism and relevance of ecological models used in chemical risk assessment. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 9(4), 907-938. doi:10.1080/713610016
Role of ecological modeling in risk assessment
Pastorok, R. A., Akçakaya, H. R., Regan, H., Ferson, S., & Bartell, S. M. (2003). Role of ecological modeling in risk assessment. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 9(4), 939-972. doi:10.1080/713610017
Treatments of uncertainty and variability in ecological risk assessment of single-species populations
Regan, H. M., Akçakaya, H. R., Ferson, S., Root, K. V., Carroll, S., & Ginzburg, L. R. (2003). Treatments of uncertainty and variability in ecological risk assessment of single-species populations. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 9(4), 889-906. doi:10.1080/713610015
2002
Uncertainty in risk analysis: Towards a general second-order approach combining interval, probabilistic, and fuzzy techniques
Ferson, S., Ginzburg, L., Kreinovich, V., Nguyen, H. T., & Starks, S. A. (2002). Uncertainty in risk analysis: Towards a general second-order approach combining interval, probabilistic, and fuzzy techniques. In PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOL 1 & 2 (pp. 1342-1347). Retrieved from https://www.webofscience.com/
Analysis and portrayal of uncertainty in a food-web exposure model
Regan, H. M., Hope, B. Y., & Ferson, S. (2002). Analysis and portrayal of uncertainty in a food-web exposure model. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 8(7), 1757-1777. doi:10.1080/20028091057592
Oberkampf, W., Helton, J., Wojtkiewicz, S., Joslyn, C., & Ferson, S. (2002). Unknown Title. Reliable Computing, 8(6), 503-505. doi:10.1023/a:1021372829139
Computing variance for interval data is NP-hard
Ferson, S., Ginzburg, L., Kreinovich, V., Longpré, L., & Aviles, M. (2002). Computing variance for interval data is NP-hard. ACM SIGACT News, 33(2), 108-118. doi:10.1145/564585.564604
Comparison of deterministic and probabilistic calculation of ecological soil screening levels
Regan, H. M., Sample, B. E., & Ferson, S. (2002). Comparison of deterministic and probabilistic calculation of ecological soil screening levels. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 21(4), 882-890. doi:2.0.CO;2">10.1897/1551-5028(2002)021<0882:CODAPC>2.0.CO;2
Bridging the gulf between ecologists and engineers
Ginzburg, L., Akcakaya, R., Ferson, S., Bridges, T., Dortch, M., & Kennedy, B. (2002). Bridging the gulf between ecologists and engineers. Proceedings of the Water Environment Federation, 2002(8), 811-838. doi:10.2175/193864702785072731
COMPARISON OF DETERMINISTIC AND PROBABILISTIC CALCULATION OF ECOLOGICAL SOIL SCREENING LEVELS
Regan, H. M., Sample, B. E., & Ferson, S. (2002). COMPARISON OF DETERMINISTIC AND PROBABILISTIC CALCULATION OF ECOLOGICAL SOIL SCREENING LEVELS. Environmental Toxicology and Chemistry, 21(4), 882. doi:2.0.co;2">10.1897/1551-5028(2002)021<0882:codapc>2.0.co;2
Combination rules in Dempster-Shafer theory
Sentz, K., & Ferson, S. (2002). Combination rules in Dempster-Shafer theory. In 6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XVI, PROCEEDINGS (pp. 191-196). Retrieved from https://www.webofscience.com/
From computation with guaranteed intervals to computation with confidence intervals: A new application of fuzzy techniques
Kreinovich, V., Nguyen, H. T., Ferson, S., & Ginzburg, L. (2002). From computation with guaranteed intervals to computation with confidence intervals: A new application of fuzzy techniques. In 2002 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY PROCEEDINGS (pp. 418-423). doi:10.1109/NAFIPS.2002.1018096
Probability bounds with uncertain input distributions and correlations
Ferson, S., & Tucker, W. T. (2002). Probability bounds with uncertain input distributions and correlations. In 6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XVI, PROCEEDINGS (pp. 186-190). Retrieved from https://www.webofscience.com/
2001
Checking for errors in calculations and software: Dimensional balance and conformance of units
Ferson, S. (2001). Checking for errors in calculations and software: Dimensional balance and conformance of units. Accountability in Research, 8(3), 261-279. doi:10.1080/08989620108573978
Setting Reliability Bounds on Habitat Suitability Indices
Burgman, M. A., Breininger, D. R., Duncan, B. W., & Ferson, S. (2001). Setting Reliability Bounds on Habitat Suitability Indices. Ecological Applications, 11(1), 70. doi:10.2307/3061056
Interval Computations as a Particular Case of a General Scheme Involving Classes of Probability Distributions
Ferson, S., Ginzburg, L., Kreinovich, V., & Schulte, H. (2001). Interval Computations as a Particular Case of a General Scheme Involving Classes of Probability Distributions. In Scientific Computing, Validated Numerics, Interval Methods (pp. 355-365). Springer US. doi:10.1007/978-1-4757-6484-0_29
Is it a crime to belong to a reference class?
Colyvan, M., Regan, H. M., & Ferson, S. (2001). Is it a crime to belong to a reference class?. JOURNAL OF POLITICAL PHILOSOPHY, 9(2), 168-181. doi:10.1111/1467-9760.00123
Setting reliability bounds on habitat suitability indices
Burgman, M. A., Breininger, D. R., Duncan, B. W., & Ferson, S. (2001). Setting reliability bounds on habitat suitability indices. ECOLOGICAL APPLICATIONS, 11(1), 70-78. doi:10.2307/3061056
Temporal variability and ignorance in Monte Carlo contaminant bioaccumulation models:: A case study with selenium in <i>Mytilus edulis</i>
Spencer, M., Fisher, N. S., Wang, W. X., & Ferson, S. (2001). Temporal variability and ignorance in Monte Carlo contaminant bioaccumulation models:: A case study with selenium in <i>Mytilus edulis</i>. RISK ANALYSIS, 21(2), 383-394. doi:10.1111/0272-4332.212119
2000
Probability Bounds Analysis Solves the Problem of Incomplete Specification in Probabilistic Risk and Safety Assessments
Ferson, S. (2001). Probability Bounds Analysis Solves the Problem of Incomplete Specification in Probabilistic Risk and Safety Assessments. In Risk-Based Decisionmaking in Water Resources IX (pp. 173-188). American Society of Civil Engineers. doi:10.1061/40577(306)16
Predicting recovery of a fish population after heavy metal impacts
Crutchfield, J., & Ferson, S. (2000). Predicting recovery of a fish population after heavy metal impacts. Environmental Science & Policy, 3, 183-189. doi:10.1016/s1462-9011(00)00049-6
Making consistent IUCN classifications under uncertainty
Akçakaya, H. R., Ferson, S., Burgman, M. A., Keith, D. A., Mace, G. M., & Todd, C. R. (2000). Making consistent IUCN classifications under uncertainty. CONSERVATION BIOLOGY, 14(4), 1001-1013. doi:10.1046/j.1523-1739.2000.99125.x
Do Unto the Environment As You Would Have the Environment Do Unto You
Ferson, S. (2000). Do Unto the Environment As You Would Have the Environment Do Unto You. Ecology, 81(7), 2054. doi:10.1890/0012-9658(2000)081[2054:duteay]2.0.co;2
Issues related to the detection of boundaries
Fortin, M. J., Olson, R. J., Ferson, S., Iverson, L., Hunsaker, C., Edwards, G., . . . Klemas, V. (2000). Issues related to the detection of boundaries. LANDSCAPE ECOLOGY, 15(5), 453-466. doi:10.1023/A:1008194205292
Variability and Measurement Error in Extinction Risk Analysis: The Northern Spotted Owl on the Olympic Peninsula
Goldwasser, L., Ferson, S., & Ginzburg, L. (n.d.). Variability and Measurement Error in Extinction Risk Analysis: The Northern Spotted Owl on the Olympic Peninsula. In Quantitative Methods for Conservation Biology (pp. 169-187). Springer-Verlag. doi:10.1007/0-387-22648-6_11
1999
When and how can you specify a probability distribution when you don't know much? II - Foundations
Anderson, E. L., Hattis, D., Matalas, N., Bier, V., Kaplan, S., Burmaster, D., . . . Ferson, S. (1999). When and how can you specify a probability distribution when you don't know much? II - Foundations. In RISK ANALYSIS Vol. 19 (pp. 47-68). doi:10.1023/A:1006954210333
New mathematical derivations applicable to safety and reliability analysis
Cooper, J. A., & Ferson, S. (1999). New mathematical derivations applicable to safety and reliability analysis. In SAFETY AND RELIABILITY, VOLS 1 & 2 (pp. 975-980). Retrieved from https://www.webofscience.com/
Using fuzzy intervals to represent measurement error and scientific uncertainty in endangered species classification
Ferson, S., Akcakaya, H. R., & Dunham, A. (1999). Using fuzzy intervals to represent measurement error and scientific uncertainty in endangered species classification. In 18TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS (pp. 690-694). doi:10.1109/NAFIPS.1999.781782
1998
Deconvolution can reduce uncertainty in risk assessment
Ferson, S., & Long, T. F. (1998). Deconvolution can reduce uncertainty in risk assessment. In RISK ASSESSMENT: LOGIC AND MEASUREMENT (pp. 325-336). Retrieved from https://www.webofscience.com/
Detecting rare event clustering in very sparse data sets
Hwang, K., & Ferson, S. (1998). Detecting rare event clustering in very sparse data sets. In PROBABILISTIC SAFETY ASSESSMENT AND MANAGEMENT (PSAM 4), VOLS 1-4 (pp. 1235-1240). Retrieved from https://www.webofscience.com/
Fuzzy regression in fisheries science: Some methods and applications
Saila, S. B., & Ferson, S. (1998). Fuzzy regression in fisheries science: Some methods and applications. In FISHERY STOCK ASSESSMENT MODELS Vol. 15 (pp. 339-354). Retrieved from https://www.webofscience.com/
Probability bounds analysis
Ferson, S., & Donald, S. (1998). Probability bounds analysis. In PROBABILISTIC SAFETY ASSESSMENT AND MANAGEMENT (PSAM 4), VOLS 1-4 (pp. 1203-1208). Retrieved from https://www.webofscience.com/
1996
Hybrid processing of stochastic and subjective uncertainty data
Cooper, J. A., Ferson, S., & Ginzburg, L. (1996). Hybrid processing of stochastic and subjective uncertainty data. RISK ANALYSIS, 16(6), 785-791. doi:10.1111/j.1539-6924.1996.tb00829.x
Different methods are needed to propagate ignorance and variability
Ferson, S., & Ginzburg, L. R. (1996). Different methods are needed to propagate ignorance and variability. RELIABILITY ENGINEERING & SYSTEM SAFETY, 54(2-3), 133-144. doi:10.1016/S0951-8320(96)00071-3
Inferring ecological risk from toxicity bioassays
Ferson, S., Ginzburg, L. R., & Goldstein, R. A. (1996). Inferring ecological risk from toxicity bioassays. In WATER AIR AND SOIL POLLUTION Vol. 90 (pp. 71-82). doi:10.1007/BF00619269
Judgment under uncertainty: Evolution may not favor a probabilistic calculus
Ginzburg, L. R., Janson, C., & Ferson, S. (1996). Judgment under uncertainty: Evolution may not favor a probabilistic calculus. BEHAVIORAL AND BRAIN SCIENCES, 19(1), 24-+. doi:10.1017/S0140525X0004125X
Automated quality assurance checks on model structure in ecological risk assessments
Ferson, S. (1996). Automated quality assurance checks on model structure in ecological risk assessments. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2(3), 558-569. doi:10.1080/10807039609383632
Inferring Ecological Risk from Toxicity BioAssays
Ferson, S., Ginzburg, L. R., & Goldstein, R. A. (1996). Inferring Ecological Risk from Toxicity BioAssays. In Clean Water: Factors that Influence Its Availability, Quality and Its Use (pp. 71-82). Springer Netherlands. doi:10.1007/978-94-009-0299-2_8
Logistic sensitivity and bounds for extinction risks
McCarthy, M. A., Burgman, M. A., & Ferson, S. (1996). Logistic sensitivity and bounds for extinction risks. In ECOLOGICAL MODELLING Vol. 86 (pp. 297-303). doi:10.1016/0304-3800(95)00067-4
What Monte Carlo methods cannot do
Ferson, S. (1996). What Monte Carlo methods cannot do. HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2(4), 990-1007. doi:10.1080/10807039609383659
1995
Hybrid arithmetic
Ferson, S., & Ginzburg, L. (n.d.). Hybrid arithmetic. In Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society (pp. 619-623). IEEE Comput. Soc. Press. doi:10.1109/isuma.1995.527766
Quality assurance for Monte Carlo risk assessment
Ferson, S. (1995). Quality assurance for Monte Carlo risk assessment. In Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (pp. 14-19).
INFERRING THREAT FROM SCIENTIFIC COLLECTIONS
BURGMAN, M. A., GRIMSON, R. C., & FERSON, S. (1995). INFERRING THREAT FROM SCIENTIFIC COLLECTIONS. CONSERVATION BIOLOGY, 9(4), 923-928. doi:10.1046/j.1523-1739.1995.09040923.x
CONSERVATIVE UNCERTAINTY PROPAGATION IN ENVIRONMENTAL RISK ASSESSMENTS
FERSON, S., & LONG, T. F. (1995). CONSERVATIVE UNCERTAINTY PROPAGATION IN ENVIRONMENTAL RISK ASSESSMENTS. In ENVIRONMENTAL TOXICOLOGY AND RISK ASSESSMENT: THIRD VOLUME Vol. 1218 (pp. 97-110). doi:10.1520/STP12686S
CORRELATIONS, DEPENDENCY BOUNDS AND EXTINCTION RISKS
FERSON, S., & BURGMAN, M. A. (1995). CORRELATIONS, DEPENDENCY BOUNDS AND EXTINCTION RISKS. BIOLOGICAL CONSERVATION, 73(2), 101-105. doi:10.1016/0006-3207(95)00047-8
Correlations, dependency bounds and extinction risks
Ferson, S. (1995). Correlations, dependency bounds and extinction risks. Biological Conservation, 73(2), 101-105. doi:10.1016/0006-3207(95)00047-8
SENSITIVITY ANALYSIS FOR MODELS OF POPULATION VIABILITY
MCCARTHY, M. A., BURGMAN, M. A., & FERSON, S. (1995). SENSITIVITY ANALYSIS FOR MODELS OF POPULATION VIABILITY. BIOLOGICAL CONSERVATION, 73(2), 93-100. doi:10.1016/0006-3207(95)00046-7
Sensitivity analysis for models of population viability
McCarthy, M. (1995). Sensitivity analysis for models of population viability. Biological Conservation, 73(2), 93-100. doi:10.1016/0006-3207(95)00046-7
The effect of the initial age-class distribution on extinction risks: Implications for the reintroduction of Leadbeater's Possum
BURGICIAN, M., FERSON, S., & LINDENMAYER, D. (1995). The effect of the initial age-class distribution on extinction risks: Implications for the reintroduction of Leadbeater's Possum. In REINTRODUCTION BIOLOGY OF AUSTRALIAN AND NEW ZEALAND FAUNA (pp. 15-20). Retrieved from https://www.webofscience.com/
1994
Risk Assessment in Conservation Biology.
Thompson, D. B. A., Burgman, M. A., Ferson, S., & Akcakaya, H. R. (1994). Risk Assessment in Conservation Biology.. The Journal of Ecology, 82(2), 428. doi:10.2307/2261313
RESPONSE OF PLANTS TO INTERACTING STRESSES (ROPIS) - PROGRAM RATIONALE, DESIGN, AND IMPLICATIONS
GOLDSTEIN, R., & FERSON, S. (1994). RESPONSE OF PLANTS TO INTERACTING STRESSES (ROPIS) - PROGRAM RATIONALE, DESIGN, AND IMPLICATIONS. JOURNAL OF ENVIRONMENTAL QUALITY, 23(3), 407-411. doi:10.2134/jeq1994.00472425002300030002x
1992
ASSESSING THE EFFECT OF COMPENSATION ON THE RISK OF POPULATION DECLINE AND EXTINCTION
GINZBURG, L. R., & FERSON, S. (1992). ASSESSING THE EFFECT OF COMPENSATION ON THE RISK OF POPULATION DECLINE AND EXTINCTION. In ESTUARINE RESEARCH IN THE 1980S (pp. 392-403). Retrieved from https://www.webofscience.com/
INTEGRATION OF ENVIRONMENTAL-MODELS IN A GEOGRAPHICAL SPREADSHEET
DOWNER, R., KURTZ, C., & FERSON, S. (1992). INTEGRATION OF ENVIRONMENTAL-MODELS IN A GEOGRAPHICAL SPREADSHEET. In COMPUTER TECHNIQUES IN ENVIRONMENTAL STUDIES IV (pp. 797-804). Retrieved from https://www.webofscience.com/
PROPAGATING UNCERTAINTY IN ECOLOGICAL RISK ANALYSIS USING INTERVAL AND FUZZY ARITHMETIC
FERSON, S., & KUHN, R. (1992). PROPAGATING UNCERTAINTY IN ECOLOGICAL RISK ANALYSIS USING INTERVAL AND FUZZY ARITHMETIC. In COMPUTER TECHNIQUES IN ENVIRONMENTAL STUDIES IV (pp. 387-401). Retrieved from https://www.webofscience.com/
QUANTITATIVE SOFTWARE TOOLS FOR CONSERVATION BIOLOGY
FERSON, S., & AKCAKAYA, H. R. (1992). QUANTITATIVE SOFTWARE TOOLS FOR CONSERVATION BIOLOGY. In COMPUTER TECHNIQUES IN ENVIRONMENTAL STUDIES IV (pp. 371-386). Retrieved from https://www.webofscience.com/
USING FUZZY ARITHMETIC IN MONTE-CARLO SIMULATION OF FISHERY POPULATIONS
FERSON, S. (1992). USING FUZZY ARITHMETIC IN MONTE-CARLO SIMULATION OF FISHERY POPULATIONS. In MANAGEMENT STRATEGIES FOR EXPLOITED FISH POPULATIONS Vol. 10 (pp. 595-608). Retrieved from https://www.webofscience.com/
1990
RECONSTRUCTIBILITY OF DENSITY DEPENDENCE AND THE CONSERVATIVE ASSESSMENT OF EXTINCTION RISKS
GINZBURG, L. R., FERSON, S., & AKCAKAYA, H. R. (1990). RECONSTRUCTIBILITY OF DENSITY DEPENDENCE AND THE CONSERVATIVE ASSESSMENT OF EXTINCTION RISKS. CONSERVATION BIOLOGY, 4(1), 63-70. doi:10.1111/j.1523-1739.1990.tb00268.x
THE DANGERS OF BEING FEW - DEMOGRAPHIC RISK ANALYSIS FOR RARE SPECIES EXTINCTION
FERSON, S., & BURGMAN, M. A. (1990). THE DANGERS OF BEING FEW - DEMOGRAPHIC RISK ANALYSIS FOR RARE SPECIES EXTINCTION. In ECOSYSTEM MANAGEMENT : RARE SPECIES AND SIGNIFICANT HABITS Vol. 471 (pp. 129-132). Retrieved from https://www.webofscience.com/
1989
EXTREME EVENT RISK ANALYSIS FOR AGE-STRUCTURED POPULATIONS
FERSON, S., GINZBURG, L., & SILVERS, A. (1989). EXTREME EVENT RISK ANALYSIS FOR AGE-STRUCTURED POPULATIONS. ECOLOGICAL MODELLING, 47(1-2), 175-187. doi:10.1016/0304-3800(89)90116-6
1987
PUTTING THINGS IN ORDER - A CRITIQUE OF DETRENDED CORRESPONDENCE-ANALYSIS
WARTENBERG, D., FERSON, S., & ROHLF, F. J. (1987). PUTTING THINGS IN ORDER - A CRITIQUE OF DETRENDED CORRESPONDENCE-ANALYSIS. AMERICAN NATURALIST, 129(3), 434-448. doi:10.1086/284647
1986
COMPETING REVIEWS, OR WHY DO CONNELL AND SCHOENER DISAGREE
FERSON, S., DOWNEY, P., KLERKS, P., WEISSBURG, M., KROOT, I., STEWART, S., . . . ANDERSON, K. (1986). COMPETING REVIEWS, OR WHY DO CONNELL AND SCHOENER DISAGREE. AMERICAN NATURALIST, 127(4), 571-576. doi:10.1086/284505
DO SYMBIOTIC PEA CRABS DECREASE GROWTH-RATE IN MUSSELS
BIERBAUM, R. M., & FERSON, S. (1986). DO SYMBIOTIC PEA CRABS DECREASE GROWTH-RATE IN MUSSELS. BIOLOGICAL BULLETIN, 170(1), 51-61. doi:10.2307/1541380
1985
MEASURING SHAPE VARIATION OF TWO-DIMENSIONAL OUTLINES
FERSON, S., ROHLF, F. J., & KOEHN, R. K. (1985). MEASURING SHAPE VARIATION OF TWO-DIMENSIONAL OUTLINES. SYSTEMATIC ZOOLOGY, 34(1), 59-68. doi:10.2307/2413345
Measuring Shape Variation of Two-dimensional Outlines
Ferson, S., Rohlf, F. J., & Koehn, R. K. (1985). Measuring Shape Variation of Two-dimensional Outlines. Systematic Biology, 34(1), 59-68. doi:10.1093/sysbio/34.1.59
1983
Image Analysis
Rohlf, F. J., & Ferson, S. (1983). Image Analysis. In Numerical Taxonomy (pp. 583-599). Springer Berlin Heidelberg. doi:10.1007/978-3-642-69024-2_68