- Gibbs sampling of the matrix Bingham-von Mises-Fisher distribution, with an application to protein interaction networks
- Fast Inference for the Latent Space Network Model Using a Case-Control Approximate Likelihood1
- Multiplicative latent factor models for description and prediction of social networks
- Modeling homophily and stochastic equivalence in symmetric relational data
- Persistent Patterns of International Michael D. Ward2
- Kruskal-Wallis and Friedman type tests for nested effects in hierarchical designs 1
- Contribution to the Discussion of "Clustering Objects on Subsets of Attributes," by Friedman and Meulman
- Modeling Dependencies in International Relations Peter D. Hoff and Michael D. Ward
- Identifying International Networks: Latent Spaces and Imputation
- Bayesian rv1ethods for Partial Stochastic Orderings Peter D. Hoff *
- A Statistical View of Learning in the Centipede Game Anton Westveld and Peter Hoff
- Nonparametric Modeling of Hierarchically Exchangeable Data Peter D. Hoff
- This is page 327 Printer: Opaque this
- A Covariance Regression Model Peter D. Hoff and Xiaoyue Niu
- Introduction and examples Models for multiway mean structure Models for separable covariance arrays Mean and covariance models for relational arrays
- Hierarchical models for multiway data Statistics, Biostatistics and the CSSS
- Hierarchical eigenmodels for matrix data Statistics, Biostatistics and the CSSS
- Latent Factor Models for Relational Data Statistics, Biostatistics and
- Latent Factor Models for Relational Data Statistics, Biostatistics and
- A primer on Bayesian statistics 1. Some philosophy on subjective probability.
- Latent SVD Models for Relational Data Statistics, Biostatistics and
- Discussion of Gelman's "Red State, Blue State" Statistics, Biostatistics and the CSSS
- Subjective probability Practical aspects Application to mortality rate estimation Summary A primer on Bayesian statistics, with an application to
- Latent Factor Models for Relational Data Statistics, Biostatistics and
- Model-based Subspace Clustering 1. Subspace clustering
- Discrete Exponential Family Models for Residential Settlement and Segregation
- Introduction and examples Modeling mean structure Modeling covariance structure Mean and Covariance Models for Tensor-Valued Data
- What is NP Bayes? Statistics, Biostatistics and the CSSS
- Invisible Men: Prison Growth and the Construction of Social
- Vitality-based Intrinsic and Extrinsic Mortality Processes Explain Patterns in Human Survival
- Latent factor models for social network data Peter Hoff and Mike Ward
- Personal Statement 1 Research statement
- Project Summary The Broad Challenge Area for this proposal is 01: Behavior, Behavioral Change and Prevention. The
- Conference Plan 1 Introduction
- BIOGRAPHICAL SKETCH Provide the following information for the key personnel and other significant contributors.
- Principal Investigator/Program Director (Last, First, Middle): BIOGRAPHICAL SKETCH
- Expectations, Markov chains, and the Metropolis algorithm Departments of Statistics and Biostatistics
- SIMUW Markov chain Monte Carlo Worksheet July 27, 2005 Darts: For throws that are uniformly distributed on the dartboard, fill in the following
- A Covariance Regression Model Peter D. Hoff1
- Hierarchical multilinear models for multiway data Peter D. Hoff 1
- A Covariance Regression Model Peter D. Hoff1
- Bayesian Methods for Partial Stochastic Orderings Peter D. Ho
- Introduction and examples Modeling mean structure Modeling covariance structure Mean and Covariance Models for Tensor-Valued Data
- Hierarchical eigenmodels for matrix data Statistics, Biostatistics and the CSSS
- LC model selection preferences CSSS, April 2010 1 / 38 Model selection in exploratory latent class &
- Research Design and Methods 1.1 Statement of the Challenge Area and the Specific Challenge Topic
- Model-based subspace clustering Statistics, Biostatistics and the CSSS
- Simulation of the matrix Bingham-von Mises-Fisher distribution, with applications to multivariate and relational data
- Constrained Nonparametric Maximum Likelihood via Mixtures Peter D. Ho
- Graduate Program Overview UW Department of Statistics
- Introduction Models based on exchangeability Homophily and stochastic equivalence Matrix decomposition models Multiway data Latent variable methods for relational data
- Factor models for relational data Real-world network sampling Mostly factor models
- Two-Sided Estimation of Mate Preferences for Similarities in Age, Education, and Religion
- Random E#ects Models for Network Data Peter D. Ho# 1
- Matrix Models for Networks, Relational and Multivariate Data
- Introduction Models based on exchangeability Homophily and stochastic equivalence Matrix decomposition models Multiway data Latent factor models for relational data
- Hierarchical eigenmodels for relational data Statistics, Biostatistics and the CSSS
- Forecasting with Imprecise Probabilities [IP] some preliminary findings Teddy Seidenfeld, Mark Schervish, and Jay Kadane Carnegie Mellon Univ.
- Modeling Dependencies in International Relations Peter D. Ho# and Michael D. Ward
- Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster
- Mixture Model Component Trees as an Alternative to High-Dimensional Cognitive
- Bilinear Mixed E#ects Models for Dyadic Data Peter D. Ho# #
- A hierarchical eigenmodel for pooled covariance estimation Peter D. Hoff 1
- Hierarchical multilinear models for multiway data Peter D. Hoff
- Marginal set likelihood for semiparametric copula estimation Peter D. Hoff
- Subset clustering of binary sequences, with an application to genomic abnormality data
- Separable covariance arrays via the Tucker product, with applications to multivariate relational data
- VMASC Statistics and Social Network Analysis Project Report Peter D. Hoff
- A Parametric Two-Sided Model of Marriage John Allen Logan, Peter D. Ho , and Michael A. Newton 1
- Bayesian Subspace Clustering 1. Subspace clustering
- Subset clustering of binary sequences, with an application to genomic abnormality data
- Dirichlet mixture models for (subspace) clustering January 28, 2005
- Constrained Nonparametric Estin1ation via Peter D. Hoff
- Model Averaging and Dimension Selection for the Singular Value Decomposition
- The Combination of Ecological and Individual-Level Data Jon Wakefield
- Latent SVD Models for Relational Data Statistics, Biostatistics and
- R. Douglas Martin Dept. of Statistics
- Introduction to Copulas Parameterization of Copulas Parameter estimation Example: Imputation of Pima diabetes data Discussion Multivariate density estimation via copulas
- Respondent-Driven Sampling: Risks and Benefits of a Novel Sampling Strategy
- Introduction and examples Modeling mean structure Modeling covariance structure Multiway Array Models for Dynamic Relational Data
- Latent Factor Models for Relational Data Statistics, Biostatistics and
- Clustering based on Dirichlet mixtures of attribute ensembles Peter D. Hoff
- A hierarchical eigenmodel for pooled covariance estimation Peter D. Hoff
- Latent SVD Models for Relational Data Statistics, Biostatistics and
- Introduction Models based on exchangeability Homophily and stochastic equivalence Matrix decomposition models Multiway data Latent factor models for relational data
- Bibliography & References Cited [1] N.A. Christakis and J.H. Fowler. The spread of obesity in a large social network over 32 years.
- exercise.smoke female.alcohol
- Bilinear Mixed Effects Models for Dyadic Data Peter D. Hoff
- Cash on delivery: An impact evaluation of India's Janani
- Clustering based on Dirichlet mixtures of attribute subsets Peter D. Hoff
- Specific Aims This project will develop statistical methods and data analysis tools for the joint statistical analysis
- The Determinants of Sex Selective Abortions Claus C Prtner
- Discussion of Handcock, Raftery and Tantrum, "Model-based clustering for social networks"
- This is page 327 Printer: Opaque this
- Random Effects Models for Network Data Peter D. Hoff1
- Hierarchical multilinear models for multiway data Peter D. Hoff 1
- Outline Model input uncertainty Model validation Bayes factors BMA: Uncertainty about model structure Summary Probabilistic Projections of HIV Prevalence
- Introduction and examples Hierarchical models for multiway factors Deep interactions International conflict Separable covariance Probability models for multiway data
- Hierarchical eigenmodels for matrix data Statistics, Biostatistics and the CSSS
- CONSTRAINED NONPARAMETRIC ESTIMATION VIA MIXTURES
- Nonparametric Modeling of Hierarchically Exchangeable Data Peter D. Ho# #
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- The Annals of Applied Statistics 2011, Vol. 5, No. 2A, 843872
- Introduction to LFMs Network locales Multiway data Latent factor models for relational data