P.D. Hoff. Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization. Computational Statistics and Data Analysis, pages 186–198, 2017. [ bib | arXiv | code ]

P.D. Hoff and Chaoyu Yu. Exact adaptive confidence intervals for linear regression coefficients. 2017. [ bib | arXiv | code ]

Maryclare Griffin and P.D. Hoff. LANOVA penalization for unreplicated data. 2017. [ bib | arXiv ]

S. Minhas, P.D. Hoff, and M.D. Ward. Influence networks in international relations. 2017. [ bib | arXiv ]

David Gerard and Peter Hoff. Adaptive higher-order spectral estimators. Electron. J. Statist., 11(2):3703–3737, 2017. [ bib | DOI | arXiv ]

Chaoyu Yu and P.D. Hoff. Adaptive multigroup confidence intervals with constant coverage. 2016. [ bib | arXiv | code ]

S. Minhas, P.D. Hoff, and M.D. Ward. Inferential Approaches for Network Analyses: AMEN for Latent Factor Models. 2016. [ bib | arXiv ]

A. Franks and P.D. Hoff. Shared subspace models for multi-group covariance estimation. 2016. [ bib | arXiv | code ]

S. Minhas, P.D. Hoff, and M.D. Ward. A new approach to analyzing coevolving longitudinal networks in international relations. Journal of Peace Research, pages 491–505, 2016. [ bib | arXiv ]

P.D. Hoff. Limitations on detecting row covariance in the presence of column covariance. J. Multivariate Anal., 152:249–258, 2016. [ bib | DOI | arXiv | code | http ]

D. Gerard and P.D. Hoff. A higher-order LQ decomposition for separable covariance models. Linear Algebra Appl., 505:57–84, 2016. [ bib | DOI | arXiv | code | http ]

P.D. Hoff. Equivariant and scale-free Tucker decomposition models. Bayesian Anal., 11(3):627–648, 2016. [ bib | DOI | arXiv | code | http ]

J.W. Harmon and P.D. Hoff. A Pivot-Based Improvement to Sandwich-Based Confidence Intervals. Technical Report 639, Department of Statistics, University of Washington, 2015. [ bib | arXiv ]

P.D. Hoff. Dyadic data analysis with amen. Technical Report 638, Department of Statistics, University of Washington, 2015. [ bib | arXiv ]

D.C. Kessler, P.D. Hoff, and D.B. Dunson. Marginally specified priors for non-parametric Bayesian estimation. J. R. Stat. Soc. Ser. B. Stat. Methodol., 77(1):35–58, 2015. [ bib | DOI | http ]

P.D. Hoff. Multilinear tensor regression for longitudinal relational data. Ann. Appl. Stat., 9(3):1169–1193, 2015. [ bib | arXiv | code ]

D. Gerard and P. Hoff. Equivariant minimax dominators of the MLE in the array normal model. J. Multivariate Anal., 137:32–49, 2015. [ bib | DOI | arXiv | code | http ]

A. Volfovsky and P.D. Hoff. Testing for Nodal Dependence in Relational Data Matrices. J. Amer. Statist. Assoc., 110(511):1037–1046, 2015. [ bib | arXiv ]

B.K. Fosdick and P.D. Hoff. Testing and Modeling Dependencies Between a Network and Nodal Attributes. J. Amer. Statist. Assoc., 110(511):1047–1056, 2015. [ bib | arXiv ]

P.D. Hoff, X. Niu, and J.A. Wellner. Information bounds for Gaussian copulas. Bernoulli, 20(2):604–622, 2014. [ bib | arXiv ]

B.K. Fosdick and P.D. Hoff. Separable factor analysis with applications to mortality data. Ann. Appl. Stat., 8(1):120–147, 2014. [ bib | arXiv ]

A. Volfovsky and P.D. Hoff. Hierarchical array priors for ANOVA decompositions of cross-classified data. Ann. Appl. Stat., 8(1):19–47, 2014. [ bib | arXiv | code ]

D.C. Kessler, P.D. Hoff, and D.B. Dunson. Marginally Specified Priors for Nonparametric Bayesian Estimation. Journal of the Royal Statistical Society, Series B, 77(1):35–58, 2014. [ bib | arXiv | code ]

X. Niu and P.D. Hoff. Simultaneous Mean and Covariance Modeling of Chronic Kidney Disease, 2013. [ bib | arXiv ]

A.H. Westveld and P.D. Hoff. Modeling of the learning process in centipede games. Stat, 2(1):242–254, 2013. [ bib | arXiv ]

P.D. Hoff, B.K. Fosdick, A. Volfovsky, and K. Stovel. Likelihoods for fixed rank nomination networks. Network Science, 1(3):253–277, 2013. [ bib | arXiv | code ]

P.D. Hoff. Bayesian analysis of matrix data with rstiefel. R-vignette, 2013. [ bib | arXiv ]

P.D. Hoff. Comment on “Bayesian Nonparametric Inference - Why and How” by Müller and Mitra. Bayesian Analysis, 8(2):311–318, 2013. [ bib | arXiv ]

P.D. Hoff and J. Wakefield. Bayesian sandwich posteriors for pseudo-true parameters. J. Statist. Plann. Inference, 143(10):1638–1642, 2013. [ bib | arXiv | code ]

A.P. Oron and P.D. Hoff. Small-Sample Behavior of Novel Phase I Cancer Trial Designs. Clinical Trials, 10(1):63–80, 2013. [ bib | arXiv ]

P.D. Hoff, B.K. Fosdick, A. Volfovsky, and K. Stovel. amen: Additive and multiplicative effects modeling of networks and relational data, 2012. [ bib | software ]

P.D. Hoff. rstiefel: Random orthonormal matrix generation on the Stiefel manifold, 2012. [ bib | software ]

A.E. Raftery, X. Niu, P.D. Hoff, and K.Y. Yeung. Fast Inference for the Latent Space Network Model Using a Case-Control Approximate Likelihood. Journal of Computational and Graphical Statistics, 21:901–919, 2012. [ bib | pdf ]

P.D. Hoff and X. Niu. A Covariance Regression Model. Statistica Sinica, 22:729–753, 2012. [ bib | arXiv | code ]

P.D. Hoff. Hierarchical multilinear models for multiway data. Computational Statistics & Data Analysis, 55:530–543, 2011. [ bib | arXiv | code ]

P.D. Hoff. Separable covariance arrays via the Tucker product, with applications to multivariate relational data. Bayesian Analysis, 6:179–196, 2011. [ bib | arXiv | code ]

A.H. Westveld and P.D. Hoff. A Mixed Effects Model for Longitudinal Relational and Network Data, with Applications to International Trade and Conflict. Annals of Applied Statistics, 5:843–872, 2011. [ bib | arXiv ]

A.P. Oron, D. Azriel, and P.D. Hoff. Dose-finding designs: the role of convergence properties. International Journal of Biostatistics, 7(1):article 39, 2011. [ bib | arXiv ]

M.P. Bronner, M. Skacel, D.A. Crispin, P.D. Hoff, M.J. Emond, L.A. Lai, R.R. Tubbs, J.N. O'Sullivan, P.S. Rabinovitch, and T.A. Brentnall. Array-based comparative genomic hybridization in ulcerative colitis neoplasia: single non-dysplastic biopsies distinguish progressors from non-progressors. Modern Pathology, 23:1624–1633, 2010. [ bib ]

P.D. Hoff. Multiplicative latent factor models for description and prediction of social networks. Computational & Mathematical Organization Theory, 15(4):261–272, 2009. [ bib | pdf ]

P.D. Hoff. A first course in Bayesian statistical methods. Springer Texts in Statistics. Springer, New York, 2009. [ bib | web ]

P.D. Hoff. Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data. Journal of Computational and Graphical Statistics, 18(2):438–456, 2009. [ bib | arXiv | code ]

P.D. Hoff. A Hierarchical Eigenmodel for Pooled Covariance Estimation. Journal of the Royal Statistical Society, Series B, 71(5):971–992, 2009. [ bib | arXiv | code ]

A.P. Oron and P.D. Hoff. The k-in-a-row Up-and-down Design, Revisited. Statistics in Medicine, 28(13):1805–1820, 2009. [ bib ]

P.N. Krivitsky, M.S. Handcock, A.E. Raftery, and P.D. Hoff. Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects models. Social networks, 31(3):204–213, 2009. [ bib | pdf ]

P.D. Hoff. Rank Likelihood Estimation for Continuous and Discrete Data. ISBA Bulletin, 15(1):8–10, 2008. [ bib | pdf | code ]

P.D. Hoff. Modeling homophily and stochastic equivalence in symmetric relational data. In J.C. Platt, D. Koller, Y. Singer, and S. Roweis, editors, Advances in Neural Information Processing Systems 20, pages 657–664. MIT Press, Cambridge, MA, 2008. [ bib | arXiv | pdf | software ]

M.D. Ward and P.D. Hoff. Analyzing Dependencies in Geo-Economics and Geo-Politics. In War, Peace and Security, pages 133–160. Emerald Group Publishing, Bingley, UK, 2008. [ bib | pdf ]

J.A. Logan, P.D. Hoff, and M.A. Newton. Two-sided estimation of mate preferences for similarities in age, education, and religion. J. Amer. Statist. Assoc., 103(482):559–569, 2008. [ bib | pdf ]

P.D. Hoff. sbgcop: Semiparametric Bayesian Gaussian copula estimation and imputation, 2007. [ bib | software ]

P.D. Hoff. eigenmodel: Semiparametric factor and regression models for symmetric relational data, 2007. [ bib | software ]

P.D. Hoff. Discussion of "Model-Based Clustering for Social Networks", by Handcock, Raftery and Tantrum. Journal of the Royal Statistical Society, Series A, 170(2):339, 2007. [ bib | pdf ]

A.P. Oron and P.D. Hoff. Kruskal-Wallis and Friedman type tests for nested effects in hierarchical designs. Technical Report 68, Center for Statistics and the Social Sciences, University of Washington, 2007. [ bib | pdf ]

C.R. Pearson, M.A. Micek, J.M. Simoni, P.D. Hoff, E. Matediana, D.P. Martin, and S.S. Gloyd. Randomized control trial of peer-delivered, modified directly observed therapy for HAART in Mozambique. JAIDS Journal of Acquired Immune Deficiency Syndromes, 46(2):238, 2007. [ bib ]

C.R. Pearson, J.M. Simoni, P. Hoff, A.E. Kurth, and D.P. Martin. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS and Behavior, 11(2):161–173, 2007. [ bib ]

CR Pearson, AE Kurth, S. Cassels, DP Martin, JM Simoni, P. Hoff, E. Matediana, and S. Gloyd. Modeling HIV transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy. AIDS care, 19(5):594–604, 2007. [ bib ]

M.D. Ward and P.D. Hoff. Persistent patterns of international commerce. Journal of Peace Research, 44(2):157, 2007. [ bib | pdf ]

P.D. Hoff. Extending the rank likelihood for semiparametric copula estimation. Ann. Appl. Stat., 1(1):265–283, 2007. [ bib | arXiv | software ]

P.D. Hoff. Model averaging and dimension selection for the singular value decomposition. J. Amer. Statist. Assoc., 102(478):674–685, 2007. [ bib | arXiv | code ]

S. Shortreed, M.S. Handcock, and P. Hoff. Positional estimation within a latent space model for networks. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 2(1):24–33, 2006. [ bib | pdf | software ]

P.D. Hoff. Model-based subspace clustering. Bayesian Anal., 1(2):321–344, 2006. [ bib | pdf | code ]

A.H. Westveld and P.D. Hoff. Statistical Methodology for Longitudinal Social Network Data. In Annual Meeting of the American Political Science Association, Washington, D.C., September 2005. American Political Science Association. [ bib | pdf ]

P.D. Hoff and M.D. Ward. Analyzing Dependencies in International Relations: Commerce, Capitalism, Conflict, Cooperation, and Democracy. In Annual Meeting of the International Studies Association, Honolulu, March 2005. International Studies Association. [ bib | pdf ]

K. Koprowicz, S.E. Emerson, and P.D. Hoff. A Comparison of Parametric and Coarsened Bayesian Interval Estimation in the Presence of a Known Mean-Variance Relationship. Technical Report 251, Department of Biotatistics, University of Washington, 2005. [ bib | pdf ]

P.D. Hoff. Subset clustering of binary sequences, with an application to genomic abnormality data. Biometrics, 61(4):1027–1036, 2005. [ bib | pdf | code ]

P.D. Hoff. Bilinear mixed-effects models for dyadic data. J. Amer. Statist. Assoc., 100(469):286–295, 2005. [ bib | pdf | code ]

P.D. Hoff and M.D. Ward. Random, Latent, and Correlated: Networks in International Relations. In Annual Meeting of the International Studies Association, Montreal, March 2004. International Studies Association. [ bib | pdf ]

P.D. Hoff. Discussion of "Clustering Objects on Subsets of Attributes", by Friedman and Meulman. Journal of the Royal Statistical Society, Series B, 66(4):845, 2004. [ bib | pdf | code ]

K.M. Haigis, P.D. Hoff, A. White, A.R. Shoemaker, R.B. Halberg, and W.F. Dove. Tumor regionality in the mouse intestine reflects the mechanism of loss of APC function. Proceedings of the National Academy of Sciences of the United States of America, 101(26):9769, 2004. [ bib ]

P.D. Hoff and M.D. Ward. Modeling dependencies in international relations networks. Political Analysis, 12(2):160–175, 2004. [ bib ]

P.D. Hoff. Random effects models for network data. In Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pages 303–312. The National Academies Press, 2003. [ bib ]

M.D Ward, P.D. Hoff, and C.L. Lofdahl. Identifying international networks: latent spaces and imputation. In Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pages 345–362. The National Academies Press, 2003. [ bib ]

P.D. Hoff. Bayesian methods for partial stochastic orderings. Biometrika, 90(2):303–317, 2003. [ bib | pdf ]

P.D. Hoff. Nonparametric estimation of convex models via mixtures. Ann. Statist., 31(1):174–200, 2003. [ bib | pdf ]

P.D. Hoff. Nonparametric Modeling of Hierarchically Exchangeable Data. Technical Report 421, Department of Statistics, University of Washington, 2003. [ bib | pdf ]

P.D. Hoff, A.E. Raftery, and M.S. Handcock. Latent space approaches to social network analysis. J. Amer. Statist. Assoc., 97(460):1090–1098, 2002. [ bib | pdf | code ]

P.D. Hoff, R.B. Halberg, A. Shedlovsky, W.F. Dove, and M.A. Newton. Identifying carriers of a genetic modifier using nonparametric Bayesian methods. In Case studies in Bayesian statistics, Vol. V (Pittsburgh, PA, 1999), volume 162 of Lecture Notes in Statist., pages 329–330. Springer, New York, 2002. [ bib ]

R.B. Halberg, D.S. Katzung, P.D. Hoff, A.R. Moser, C.E. Cole, R.A. Lubet, L.A. Donehower, R.F. Jacoby, and W.F. Dove. Tumorigenesis in the multiple intestinal neoplasia mouse: redundancy of negative regulators and specificity of modifiers. Proceedings of the National Academy of Sciences of the United States of America, 97(7):3461, 2000. [ bib ]

P.D. Hoff. Constrained nonparametric maximum likelihood via mixtures. J. Comput. Graph. Statist., 9(4):633–641, 2000. [ bib | pdf ]

P.D. Hoff. Constrained Nonparametric Estimation via Mixtures. PhD thesis, University of Wisconsin-Madison, Madison, Wisconsin, 2000. [ bib | pdf ]

L.A. Shepel, H. Lan, J.D. Haag, G.M. Brasic, M.E. Gheen, J.S. Simon, P. Hoff, M.A. Newton, and M.N. Gould. Genetic identification of multiple loci that control breast cancer susceptibility in the rat. Genetics, 149(1):289, 1998. [ bib ]