Most of my articles since 2006 are available on arXiv.
P. Hoff. Bayes-optimal prediction with frequentist coverage control. Bernoulli, 29(2):901–928, 2023. [ bib | DOI | arXiv | code ]
J.G. Bryan and P.D. Hoff. Smaller p-values in genomics studies using distilled auxiliary information. Biostatistics, 24(1):193–208, 2023. [ bib | DOI | arXiv | http ]
Andrew McCormack and Peter D. Hoff. Tests of linear hypotheses using indirect information. Canad. J. Statist., 51(3):852–876, 2023. [ bib | arXiv ]
A. McCormack and P. D. Hoff. Equivariant estimation of Fréchet means. Biometrika, 110(4):1055–1076, 2023. [ bib | DOI | arXiv | http ]
J.G. Bryan, P.D. Hoff, and C.L. Osburn. Routine Estimation of Dissolved Organic Matter Sources Using Fluorescence Data and Linear Least Squares. ACS ES&T Water, 3(8):1972–2808, 2023. [ bib | DOI | http ]
E. Bersson and P.D. Hoff. Frequentist prediction sets for species abundance using indirect information. 2023. [ bib | arXiv ]
J.G. Bryan and P.D. Hoff. Linear source apportionment using generalized least squares. 2023. [ bib | arXiv ]
E. Bersson and P.D. Hoff. Bayesian Covariance Estimation for Multi-group Matrix-variate Data. 2023. [ bib | arXiv | code ]
A. McCormack and P.D. Hoff. Information geometry and asymptotics for Kronecker covariances. 2023. [ bib | arXiv ]
P.D. Hoff. Smaller p-values via indirect information. J. Amer. Statist. Assoc., 117(539):1254–1269, 2022. [ bib | DOI | arXiv | code | http ]
P.D. Hoff. Coverage properties of empirical Bayes intervals: A discussion of “Confidence intervals for nonparametric empirical Bayes analysis” by Ignatiadis and Wager. J. Amer. Statist. Assoc., 117(539):1175–1178, 2022. [ bib | DOI | arXiv | http ]
A. McCormack and P. Hoff. The Stein effect for Fréchet means. Ann. Statist., 50(6):3647–3676, 2022. [ bib | DOI | arXiv ]
P.D. Hoff, A. McCormack, and A.R. Zhang. Core shrinkage covariance estimation for matrix-variate data. Journal of the Royal Statistical Society, Series B, to appear, 2022. [ bib | arXiv | code ]
E. Bersson and P.D. Hoff. Optimal conformal prediction for small areas. Journal of Survey Statistics and Methodology, to appear, 2022. [ bib | arXiv | code ]
M.F. Christensen and P.D. Hoff. A nonstationary spatial covariance model for data on graphs. 2022. [ bib | arXiv ]
M. Jauch, P.D. Hoff, and D.B. Dunson. Monte Carlo simulation on the Stiefel manifold via polar expansion. J. Comput. Graph. Statist., 30(3):622–631, 2021. [ bib | DOI | arXiv | code | http ]
P.D. Hoff. Additive and multiplicative effects network models. Statist. Sci., 36(1):34–50, 2021. [ bib | DOI | arXiv | code | http ]
M. Drton, S. Kuriki, and P. Hoff. Existence and uniqueness of the Kronecker covariance MLE. Ann. Statist., 49(5):2721–2754, 2021. [ bib | DOI | arXiv | http ]
J. Mulder and P.D. Hoff. A latent variable model for relational events with multiple receivers. Annals of Applied Statistics, to appear, 2021. [ bib | arXiv ]
J.G. Bryan, J. Niles-Weed, and P.D. Hoff. The multirank likelihood for semiparametric canonical correlation analysis. 2021. [ bib | arXiv ]
M. Jauch, P.D. Hoff, and D.B. Dunson. Random orthogonal matrices and the Cayley transform. Bernoulli, 26(2):1560–1586, 2020. [ bib | DOI | arXiv | code | http ]
K. Burris and P.D. Hoff. Exact adaptive confidence intervals for small areas. Journal of Survey Statistics and Methodology, 8(2):206–230, 2020. [ bib | arXiv | code ]
M. Griffin and P.D. Hoff. Testing sparsity-inducing penalties. J. Comput. Graph. Statist., 29(1):128–139, 2020. [ bib | DOI | arXiv ]
A.K. Yanchenko and P.D. Hoff. Hierarchical multidimensional scaling for the comparison of musical performance styles. Ann. Appl. Stat., 14(4):1581–1603, 2020. [ bib | DOI | arXiv | http ]
X. Niu and P.D. Hoff. Joint mean and covariance modeling of multiple health outcome measures. Ann. Appl. Stat., 13(1):321–339, 2019. [ bib | DOI | arXiv | http ]
S. Minhas, P.D. Hoff, and M.D. Ward. Inferential approaches for network analyses: AMEN for latent factor models. Political Analysis, 27:208–222, 2019. [ bib | DOI | arXiv ]
M. Griffin and P.D. Hoff. Lasso ANOVA decompositions for matrix and tensor data. Comput. Statist. Data Anal., 137:181–194, 2019. [ bib | DOI | arXiv | http ]
Y. He and P.D. Hoff. Multiplicative coevolution regression models for longitudinal networks and nodal attributes. Social Networks, 57:54–62, 2019. [ bib | arXiv | code ]
P.D. Hoff and C. Yu. Exact adaptive confidence intervals for linear regression coefficients. Electron. J. Stat., 13(1):94–119, 2019. [ bib | DOI | arXiv | code | http ]
C. Yu and P.D. Hoff. Adaptive sign error control. J. Statist. Plann. Inference, 201:133–145, 2019. [ bib | DOI | arXiv | http ]
A.M. Franks and P.D. Hoff. Shared subspace models for multi-group covariance estimation. J. Mach. Learn. Res., 20:Paper No. 171, 37, 2019. [ bib | arXiv | code ]
M. Griffin and P.D. Hoff. Structured shrinkage priors. Journal of Computational and Graphical Statistics, to appear, 2019. [ bib | arXiv | code ]
C. Yu and P. D. Hoff. Adaptive multigroup confidence intervals with constant coverage. Biometrika, 105(2):319–335, 2018. [ bib | DOI | arXiv | code | http ]
S. Minhas, P.D. Hoff, and M.D. Ward. Influence networks in international relations. 2017. [ bib | arXiv ]
D. Gerard and P.D. Hoff. Adaptive higher-order spectral estimators. Electron. J. Statist., 11(2):3703–3737, 2017. [ bib | DOI | arXiv ]
P.D. Hoff. Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization. Comput. Statist. Data Anal., 115:186–198, 2017. [ 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 ]
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. Limitations on detecting row covariance in the presence of column covariance. J. Multivariate Anal., 152:249–258, 2016. [ bib | DOI | arXiv | code | http ]
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 ]
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 ]
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 ]
D. Gerard and P.D. Hoff. Equivariant minimax dominators of the MLE in the array normal model. J. Multivariate Anal., 137:32–49, 2015. [ bib | DOI | arXiv | code | http ]
P.D. Hoff. Multilinear tensor regression for longitudinal relational data. Ann. Appl. Stat., 9(3):1169–1193, 2015. [ bib | arXiv | code ]
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 | arXiv | http ]
P.D. Hoff. Dyadic data analysis with amen. Technical Report 638, Department of Statistics, University of Washington, 2015. [ bib | arXiv ]
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 ]
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 ]
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 ]
P.D. Hoff, X. Niu, and J.A. Wellner. Information bounds for Gaussian copulas. Bernoulli, 20(2):604–622, 2014. [ bib | arXiv ]
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 and J. Wakefield. Bayesian sandwich posteriors for pseudo-true parameters. J. Statist. Plann. Inference, 143(10):1638–1642, 2013. [ bib | arXiv | code ]
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. Bayesian analysis of matrix data with rstiefel. R-vignette, 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 ]
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 and X. Niu. A covariance regression model. Statistica Sinica, 22:729–753, 2012. [ bib | arXiv | code ]
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. rstiefel: Random orthonormal matrix generation on the Stiefel manifold, 2012. [ bib | software ]
P.D. Hoff, B.K. Fosdick, A. Volfovsky, and Y. He. amen: Additive and multiplicative effects modeling of networks and relational data, 2012. [ bib | software ]
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 ]
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 ]
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 ]
P.D. Hoff. Hierarchical multilinear models for multiway data. Computational Statistics & Data Analysis, 55:530–543, 2011. [ bib | arXiv | code ]
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.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 ]
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.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 ]
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 first course in Bayesian statistical methods. Springer Texts in Statistics. Springer, New York, 2009. [ bib | web ]
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 ]
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 ]
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 ]
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 ]
P.D. Hoff. Rank likelihood estimation for continuous and discrete data. ISBA Bulletin, 15(1):8–10, 2008. [ bib | pdf | code ]
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 ]
P.D. Hoff. Extending the rank likelihood for semiparametric copula estimation. Ann. Appl. Stat., 1(1):265–283, 2007. [ bib | arXiv | software ]
M.D. Ward and P.D. Hoff. Persistent patterns of international commerce. Journal of Peace Research, 44(2):157, 2007. [ bib | pdf ]
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 ]
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 ]
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 ]
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 ]
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 ]
P.D. Hoff. eigenmodel: Semiparametric factor and regression models for symmetric relational data, 2007. [ bib | software ]
P.D. Hoff. sbgcop: Semiparametric Bayesian Gaussian copula estimation and imputation, 2007. [ bib | software ]
P.D. Hoff. Model-based subspace clustering. Bayesian Anal., 1(2):321–344, 2006. [ bib | pdf | 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 ]
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 ]
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. Subset clustering of binary sequences, with an application to genomic abnormality data. Biometrics, 61(4):1027–1036, 2005. [ bib | pdf | code ]
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 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 and M.D. Ward. Modeling dependencies in international relations networks. Political Analysis, 12(2):160–175, 2004. [ bib ]
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. 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 ]
P.D. Hoff. Nonparametric modeling of hierarchically exchangeable data. Technical Report 421, Department of Statistics, University of Washington, 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. Bayesian methods for partial stochastic orderings. Biometrika, 90(2):303–317, 2003. [ bib | pdf ]
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. 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 ]
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 ]
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. Constrained Nonparametric Estimation via Mixtures. PhD thesis, University of Wisconsin-Madison, Madison, Wisconsin, 2000. [ bib | pdf ]
P.D. Hoff. Constrained nonparametric maximum likelihood via mixtures. J. Comput. Graph. Statist., 9(4):633–641, 2000. [ bib | pdf ]
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 ]
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 ]