| Toryn Schafer

Haoxuan Wu, Toryn L.J. Schafer, David S. Matteson (2024). Trend and Variance Adaptive Bayesian Changepoint Analysis and Local Outlier Scoring. Journal of Business & Economic Statistics, (0), pp. 1–21, https://doi.org/10.1080/07350015.2024.2362269.

Haoxuan Wu, Toryn L. J. Schafer, Sean Ryan, David S. Matteson (2024). Drift vs Shift: Decoupling Trends and Changepoint Analysis. Technometrics, (0), pp. 1–16, https://doi.org/10.1080/00401706.2024.2365730.

Stephanie A. Cunningham, Toryn L. J. Schafer, Christopher K. Wikle, Jay A. VonBank, Bart M. Ballard, Lei Cao, Stuart Bearhop, Anthony D. Fox, Geoff M. Hilton, Alyn J. Walsh, Larry R. Griffin, Mitch D. Weegman (2023). Time-varying effects of local weather on behavior and probability of breeding deferral in two Arctic-nesting goose populations. Oecologia, (201), pp. 369–383, https://doi.org/10.1007/s00442-022-05300-x.

Toryn L. J. Schafer, David S. Matteson (2023). Locally Adaptive Shrinkage Priors for Trends and Breaks in Count Time Series. NA.

Jay A. VonBank, Toryn L. J. Schafer, Stephanie A. Cunningham, Mitch D. Weegman, Paul T. Link, Kevin J. Kraai, Christopher K. Wikle, Daniel P. Collins, Lei Cao, Bart M. Ballard (2023). Joint use of location and acceleration data reveals influences on transitions among habitats in wintering birds. Scientific Reports, (13), pp. 2132, https://doi.org/10.1038/s41598-023-28937-x.

Matthew Davidow, Toryn L. J. Schafer, Cory Merow, Judy Che-Castaldo, Marie-Christine Duker, Emily Feng, David S. Matteson (2023). Clustering future scenarios based on predicted range maps. Methods in Ecology and Evolution, (14), pp. 1346-1360, https://doi.org/https://doi.org/10.1111/2041-210X.14080.

Olukunle O. Owolabi, Toryn L. J. Schafer, G.E. Smits, S. Sengupta, S. Ryan, Lan Wang, David S. Matteson, Mila Getmansky Sherman, Deborah A. Sunter (2022). Role of variable renewable energy penetration on electricity price and its volatility across independent system operators in the United States. Data Science in Science.

Alexander R. Schindler, Stephanie A. Cunningham, Toryn L. J. Schafer, Emily A. Sinnott, Sarah J. Clements, Frances M. DiDonato, Alisha R. Mosloff, Clay M. Walters, Amy A. Shipley, Mitch D. Weegman, Qing Zhao (2022). Joint analysis of structured and semi-structured community science data improves precision of relative abundance but not trends in birds. Scientific Reports, (12), pp. 20289, https://doi.org/10.1038/s41598-022-23603-0.

Matthew Davidow, Cory Merow, Judy Che-Castaldo, Toryn L. J. Schafer, Marie-Christine Duker, Derek Corcoran, David Matteson (2022). Clustering Future Scenarios Based on Predicted Range Maps. Accepted at Methods for Ecology and Evolution.

Toryn L. J. Schafer, Christopher K. Wikle, Mevin B. Hooten (2022). Bayesian Inverse Reinforcement Learning for Collective Animal Movement. The Annals of Applied Statistics, (16), pp. 999 – 1013, https://doi.org/10.1214/21-AOAS1529.

Mei-Ling E Feng, Olukunle O Owolabi, Toryn L J Schafer, Sanhita Sengupta, Lan Wang, David S Matteson, Judy P Che-Castaldo, Deborah A Sunter (2022). Analysis of animal-related electric outages using species distribution models and community science data. Environmental Research: Ecology, (1), pp. 011004, https://doi.org/10.1088/2752-664X/ac7eb5.

Mei-Ling E. Feng, Olukunle O. Owolabi, Toryn L. J. Schafer, Sanhita Sengupta, Lan Wang, David S. Matteson, Judy P. Che-Castaldo, Deborah A. Sunter (2022). Analysis of animal-related electric outages using species distribution models and community science data. Environmental Research: Ecology.

Toryn L. J. Schafer, Ryan M. McGranaghan, Mila Getmansky Sherman, Mei-Ling E. Feng, Olukunle O. Owolabi, Sean E. Ryan, Marie-Christine Duker, Michael Jauch, David S. Matteson (2021). Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 4155–4156, https://doi.org/10.1145/3447548.3469480.

Jay A. VonBank, Toryn L. J. Schafer, Stephanie A. Cunningham, Mitch D. Weegman, Paul T. Link, Kevin J. Kraai, Christopher K. Wikle, Daniel P. Collins, Lei Cao, Bart M. Ballard (2021). Joint use of location and acceleration data reveals drivers of transitions among habitats in wintering birds. Under Revision at Scientific Reports.

Erin M. Schliep, Toryn L. J. Schafer, Matthew Hawkey (2021). Distributed lag models to identify the cumulative effects of training and recovery in athletes using multivariate ordinal wellness data. Journal of Quantitative Analysis in Sports, (17), pp. 241–254, https://doi.org/doi:10.1515/jqas-2020-0051.

Toryn L. J. Schafer, Christopher K. Wikle, Jay A. VonBank, Bart M. Ballard, Mitch D. Weegman (2020). A Bayesian Markov Model with P{o}lya-Gamma Sampling for Estimating Individual Behavior Transition Probabilities from Accelerometer Classifications. Journal of Agricultural, Biological and Environmental Statistics, (25), pp. 365–382, https://doi.org/10.1007/s13253-020-00399-y.

Toryn L. J. Schafer, Christopher K. Wikle (2019). Alternative Learning Strategies for Realistic Collective Animal Movement. JSM Proceedings, Section on Statistics and the Environment. Alexandria, VA: American Statistical Association, pp. 2936–2944.

Toryn L. J. Schafer, Stewart W. Breck, Sharon Baruch-Mordo, David L. Lewis, Kenneth R. Wilson, Julie S. Mao, Thomas L. Day (2018). American black bear den-site selection and characteristics in an urban environment. Ursus, (29), pp. 25 – 31, https://doi.org/10.2192/URSUS-D-17-00004.2.