Peterson, R. A. and Cavanaugh, J. E. (2022). Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials. To appear in AStA Advances in Statistical Analysis; available online at https://doi.org/10.1007/s10182-021-00431-7.

Burghardt, E., Sewell, D. and Cavanaugh, J. (2022). Agglomerative and divisive hierarchical Bayesian clustering. To appear in Computational Statistics and Data Analysis; available online at https://doi.org/10.1016/j.csda.2022.107566.

Riedle, B., Neath, A. A. and Cavanaugh, J. E. (2020). Reconceptualizing the p–value from a likelihood ratio test: a probabilistic pairwise comparison of models based on Kullback–Leibler discrepancy measures. Journal of Applied Statistics, 47, 2582–2609. (doi:10.1080/02664763.2020.1754360)

Peterson, R. A. and Cavanaugh, J. E. (2020). Ordered quantile normalization: a semiparametric transformation built for the cross–validation era. Journal of Applied Statistics, 47, 2312–2327. (doi:10.1080/02664763.2019.1630372)

Cavanaugh, J. E. and Neath, A. A. (2019). The Akaike information criterion: Background, derivation, properties, application, interpretation, and refinements. WIREs Computational Statistics, 11:e1460. (doi:10.1002/wics.1460)

Zhang, F., & Chan, K. S. (2022). Random projection ensemble classification with high‐dimensional time series. To appear in Biometrics.

Meng, J., & Chan, K. S. (2022). Penalized quasi-likelihood estimation of generalized Pareto regression–consistent identification of risk factors for extreme losses. Insurance: Mathematics and Economics, 104, 60-75.

Wang, C., & Chan, K. S. (2018). Quasi-likelihood estimation of a censored autoregressive model with exogenous variables. Journal of the American Statistical Association, 113(523), 1135-1145.

Su, F., & Chan, K. S. (2017). Testing for threshold diffusion. Journal of Business & Economic Statistics, 35(2), 218-227.

Stenseth, N. C., Chan, K. S., Tong, H., Boonstra, R., Boutin, S., Krebs, C. J., ... & Hurrell, J. W. (1999). Common dynamic structure of Canada lynx populations within three climatic regions. Science, 285(5430), 1071-1073.

Xun Li, Joyee Ghosh, and Gabriele Villarini, (2023+)"A Comparison of Bayesian Multivariate Versus Univariate Normal Regression Models for Prediction", The American Statistician, To Appear.

Xun Li, Joyee Ghosh, and Gabriele Villarini, (2023+) "Bayesian Negative Binomial Regression Model With Unobserved Covariates for Predicting the Frequency of North Atlantic Tropical Storms", Journal of Applied Statistics, To Appear.

Joyee Ghosh (2019), "Cauchy and Other Shrinkage Priors for Logistic Regression in the Presence of Separation" , Wiley Interdisciplinary Reviews: Computational Statistics, 11(6), e1478.

Gabriele Villarini, Beda Luitel, Gabriel A. Vecchi, and Joyee Ghosh (2019) "Multi-model ensemble forecasting of North Atlantic tropical cyclone activity", Climate Dynamics, 53(12), 7461-7477.

Joyee Ghosh, Yingbo Li , and Robin Mitra (2018), "On the use of Cauchy prior distributions for Bayesian logistic regression", Bayesian Analysis, 13(2), 359-383.

Martinez A, Awad AM, Jones MP, Hornbuckle KC. (2022). Intracity occurrence and distribution of airborne PCB congeners in Chicago. Science of the Total Environment 812:151505.

Hill CM, Jones MP, Chi DL. (2022). Effects of Adult Medicaid Dental Benefits Elimination on Child Dental Care Use. Medical Care 60(8):579-587.

Hongqian Wu, Jones MP. (2021). Proportional likelihood ratio mixed model for discrete longitudinal data. Statistics in Medicine 40:2272-2285.

Lou Y, Jones MP, Sun W. (2019). Assessing the ratio of means as a causal estimand in clinical endpoint bioequivalence studies in the presence of intercurrent events. Statistics in Medicine 38:5214-5235.

Jones MP (2018). Linear regression with left-censored covariates and outcome using a pseudo-likelihood approach. Environmetrics, 29(8), e2536, p.1-16.

Lang, J.B. (2023). A Randomization P-Value Test for Detecting Copying on Multiple-Choice Exams. Journal of Educational and Behavioral Statistics, 48(3): 296-319.

Levchak, Philip, Karen Heimer, Joseph B. Lang and Janet L. Lauritsen. (2022). “Race and Trends in Men’s Imprisonment in the United States.” British Journal of Criminology. 62(5): 1233-1251. DOI: 10.1093/bjc/azac049

Zhu, Q. and Lang, J.B. (2022). Test-Inversion Confidence Intervals for Estimands in Contingency Tables Subject to Equality Constraints. Computational Statistics and Data Analysis, 169 (2022): 107413. https://doi.org/10.1016/j.csda.2021.107413

Lauritsen, J., Heimer, K., Lang, J. B. (2018). The Enduring Significance of Racial and Ethnic Disparities in Male Violent Victimization: An Analysis of National Crime Survey Victimization Data, 1973-2010. DuBois Review, 69-87.

Lang, J. B. (2017). Mean-Minimum Exact Confidence Intervals. The American Statistician, 71(4), 354-368.

H.U. Gerber and E.S.W. Shiu (2021). Equivalence Principle and Jewell's Inequality, European Actuarial Journal, 11, 725-730.

H.U. Gerber, E.S.W. Shiu and J. Yang (2021). An Actuarial Approach to Pricing Barrier Options. European Actuarial, 11, 333-339. Journal. https://doi.org/10.1007/s13385-021-00266-1

E.S.W. Shiu and X. Xiong (2021). An Elementary Derivation of Hattendorff’s Theorem. European Actuarial Journal, 11, 319-323. https://doi.org/10.1007/s13385-020-00256-9

H.U. Gerber, E.S.W. Shiu and H. Yang (2019). A Constraint-free Approach to Optimal Reinsurance. Scandinavian Actuarial Journal, 67-92.

H.U. Gerber, E.S.W. Shiu and H. Yang (2015). Geometric Stopping of a Random Walk and Its Applications to Valuing Equity-linked Death Benefits. Insurance: Mathematics and Economics, 64, 313–325.

Hong Beng Lim and Shyamalkumar, N. D. (2020). A Semiparametric Method for Assessing Life Expectancy Evaluations, North American Actuarial Journal (available online; 35 pages).

Shyamalkumar, N. D. and Tao, Siyang (2020). On Tail Dependence Matrices: The Realization Problem for Parametric Families, Extremes, 23, 245-285.

Ahn, J. Y. and Shyamalkumar, N. D. (2014). Asymptotic Theory for the Empirical Haezendonck-Goovaerts Risk Measure, Insurance: Mathematics and Economics, 55, No. 1, 78-90.

Chakraborty, I. and Shyamalkumar N. D. (2014) Revenue and Efficiency Ranking in Large Multi-Unit and Bundle Auctions, Journal of Mathematical Economics, 50, 12-21.

Russo, R. P. and Shyamalkumar, N. D. (2007). Reading Policies for Joins: An Asymptotic Analysis, Annals of Applied Probability, 17, 230-264.

Srivastava, S. and Xu, Y. (2021). Distributed Bayesian Inference for Linear Mixed-Effects Models. Journal of Computational and Graphical Statistics.

Srivastava, S., DePalma, G., and C. Liu (2019). Journal of Computational and Graphical Statistics 28 (2), 233-243.

Srivastava, S., Li, C., and Dunson, D.B. (2018). Scalable Bayes via Barycenter in Wasserstein Space. The Journal of Machine Learning Research, 19 (1), 312–346.

Li, C., Srivastava, S., and Dunson, D. B. (2017). PIE: simple, scalable and accurate posterior interval estimation. Biometrika 104 (3), 665–680.

Srivastava, S., Engelhardt, B. E., and Dunson, D. B. (2017). Expandable factor analysis. Biometrika 104 (3), 649–663.

Im, Y., Huang, Y., Tan, A., and Ma, S. (2023) Bayesian finite mixture of regression analysis for cancer based on histopathological imaging-environment interactions. Biostatistics.

Im, Y. and Tan, A. (2021) Bayesian subgroup analysis in regression using mixture models. Computational Statistics and Data Analysis, 162.

Jin, R. and Tan, A. (2021). Fast Markov chain Monte Carlo for high dimensional Bayesian regression models with shrinkage priors. Journal of Computational and Graphical Statistics.

Liu, R. and Tan, A. (2020). Towards Interpretable Automated Machine Learning for STEM Career Prediction. Journal of Educational Data Mining, 12(2), 19-32.

Roy, V., Tan, A. and Flegal, J. (2018). Estimating standard errors for importance sampling estimators with multiple Markov chains. Statistica Sinica, 28, 1079-1101.

Andrew M. Thomas (2023). Central limit theorems and asymptotic independence for local U-statistics on diverging halfspaces. Bernoulli, 29(4), 3280-3306.

Andrew M. Thomas, Peter A. Crozier, Yuchen Xu, and David S. Matteson (2023). Feature detection and hypothesis testing for extremely noisy nanoparticle images using topological data analysis. Technometrics, link.

Andrew M. Thomas (2022). The VC-dimension of a class of multiples of the primes, and a connection to AdaBoost. Online Journal of Analytic Combinatorics, 17, link.

Andrew M. Thomas and Takashi Owada (2021). Functional strong laws of large numbers for Euler characteristic processes of extreme sample clouds. Extremes, 24(4), 699-724.

Andrew M. Thomas and Takashi Owada (2021). Functional limit theorems for the Euler characteristic process in the critical regime. Advances in Applied Probability, 53(1), 57-80.

 

Tierney, L., “Dynamic and Interactive Graphics in Lisp-Stat,” in JSM Proceedings, Statistical Graphics Section, Alexandria, VA: American Statistical Association, 134–140, 2017.

Feng, D., Liang, D., and Tierney, L., “A unified Bayesian hierarchical model for MRI tissue classification,” Statistics in Medicine 33, 1349–1368, 2013.

Feng, D., Tierney, L., and Magnotta, V., “MRI Tissue Classification using High Resolution, Bayesian Hidden Markov Normal Mixture Models,” J. A. S. A. 107, 102–129, 2012.

Feng, D. and Tierney, L., “mritc: A Package for MRI Tissue Classification,” Journal of Statistical Software, Vol. 44, Issue 7, Oct 2011.

Luke Tierney, “Lisp-Stat,” Wiley Interdisciplinary Reviews: Computational Statistics, 2,

626–630, 2010.

Gómez, F., Tang, Q., and Tong, Z., 2022. The Gradient Allocation Principle based on the Higher Moment Risk Measure. Journal of Banking and Finance, 143, 106544. https://doi.org/10.1016/j.jbankfin.2022.106544.

Tang, Q., Tong, Z., and Xun, L., 2022. Insurance Risk Analysis of Financial Networks Vulnerable to a Shock. European Journal of Operational Research, 301(2), pp.756–771. https://doi.org/10.1016/j.ejor.2021.11.017.

Tang, Q., Tong, Z., and Xun, L., 2022. Portfolio Risk Analysis of Excess of Loss Reinsurance. Insurance: Mathematics and Economics, 102, pp.91–110. https://doi.org/10.1016/j.insmatheco.2021.11.004.

Tang, Q., Tong, Z., and Yang, Y., 2021. Large Portfolio Losses in a Turbulent Market. European Journal of Operational Research, 292(2), pp.755–769. https://doi.org/10.1016/j.ejor.2020.10.043.

Hao, B., Wang, B., Wang, P., Zhang, J., Yang, J., Sun, W. (2021) Sparse tensor additive regression. Journal of Machine Learning Research, 22(64), 1-43..

Wang, B. and Zou, H. (2019) A multicategory kernel distance weighted discrimination method for multiclass classification. Technometrics, 61(3), 396-408.

Wang, B. and Zou, H. (2018) Another look at distance-weighted discrimination. Journal of the Royal Statistical Society, Series B, 80(1), 177-198.

Koerner, T., Zhang, Y., Nelson, P., Wang, B., Zou, H. (2017) Neural indices of phonemic discrimination and sentence-level speech intelligibility in quiet and noise: A P3 study. Hearing Research, 350, 58-67.

Wang, B. and Zou, H. (2016) Sparse distance weighted discrimination. Journal of Computational and Graphical Statistics, 25(3), 826-838.

Wikle, N.B., Zigler, C.M. (2024+) Causal health impacts of power plant emission controls under mod[1]eled and uncertain physical process interference. Accepted to Annals of Applied Statistics, arXiv.

Wikle, N.B., Hanks, E.M., Henneman, L.R.F., and Zigler, C.M. (2022) A mechanistic model of annual sulfate concentrations in the United States. Journal of the American Statistical Association. 117(539), 1082–1093. doi:10.1080/01621459.2022.2027774, link.

Tran, T.N.*, Wikle, N.B.*, Hanks, E.M., Boni, M.F. [and 10 others]. (2022) SARS-CoV-2 attack rate and population immunity in southern New England, March 2020 to May 2021. JAMA Network Open. 5(5):e2214171. doi:10.1001/jamanetworkopen.2022.14171, link.

Wikle, N.B.*, Tran, T.N.*, Hanks, E.M., Boni, M.F. [and 12 others]. (2022) SARS-CoV-2 epidemic after social and economic reopening in three US states reveals shifts in age structure and clinical characteristics. Science Advances. 8(4). doi:10.1126/sciadv.abf9868, link.

Tran, T.N., Wikle, N.B., Hanks, E.M., Boni, M.F. [and 11 others]. (2021) Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts. BMC Medicine,

19(162). doi:10.1186/s12916-021-02038-w, link.

*  Indicates co-first authorship.

Zimmerman, D.L. and Ver Hoef, J.M. (2022). On deconfounding spatial confounding in linear models. The American Statistician, 76, 159–167.

Song, R. and Zimmerman, D.L. (2021). Modelling spatial correlation that grows on trees, with a stream network application. Spatial Statistics, https://doi.org/10.1016/j.spasta.2021.100536

Karl, A.T. and Zimmerman, D.L. (2021). A diagnostic for bias in linear mixed model estimators induced by dependence between the random effects and the corresponding model matrix. Journal of Statistical Planning and Inference, 211, 107–118.

Zimmerman, D.L. and Lim, H.B. (2021). The middle-seed anomaly: Why does it occur in some sports tournaments but not others? Journal of Quantitative Analysis in Sports, 17, 171–185.

Zimmerman, D.L., Zimmerman, N.D., and Zimmerman, J.T. (2021). March Madness “Anomalies”: Are they real, and if so, can they be explained? The American Statistician, 75, 207–216.