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NSF-CBMS Regional Conference Series in Probability and Statistics

This series is co-published by the IMS and the American Statistical Association.

Please contact the Dues and Subscriptions Office to place your order. You can order online or download a pdf order form.

Vol

Title
Authors / Editors
Description

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9

Nonparametric Bayesian Inference

Peter Müller and Abel Rodriguez

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Project Euclid

This volume can be purchased through IMS

These notes arose out of a short course at UC Santa Cruz in summer 2010. Like the course, the notes provide an overview of some popular Bayesian nonparametric (BNP) probability models. The discussion follows a logical development of many commonly used nonparametric Bayesian models as generalizations of the Dirichlet process (DP) in different directions, including Pólya tree (PT) models, species sampling models (SSM), dependent DP (DDP) models and product partition models (PPM). The selection of topics is subjective, simply driven by what the authors are familiar with. As a result, some useful and elegant classes of models such as normalized random measures with random increments (NRMIs) are reviewed only briefly.

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8

Analysis of Longitudinal and Cluster-Correlated Data

Nan Laird, Harvard University

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The analysis of data with outcomes measured repeatedly on each subject has experienced several transforming developments in the last twenty years. This monograph presents a unified treatment of modern methods for longitudinal and/or correlated data that have developed during this period. The basic approach that the author takes to modeling longitudinal data is to extend familiar univariate regression models to multivariate or correlated outcomes. The author deals with linear models for measured data and generalized linear models for binary and count data. The author shows how methods can accommodate missing outcomes and/or unbalanced designs. Both likelihood and moment methods of estimation are covered, as are random effects approaches to data modeling and parameter estimation. The monograph assumes that the reader has a solid foundation in statistical inference, linear and generalized linear regression models, and a basic knowledge of multivariate methods. It is appropriate for second year doctoral students or postdoctoral fellows in Statistics/Biostatistics as well as researchers or faculty interested in learning about the field.

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7

Generalized Linear Mixed Models

Charles E. McCulloch

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Generalized Linear Mixed Models explores the idea of statistical models that incorporate random factors into generalized linear models. This accommodates correlated data, nonlinear models and non-normally distributed responses. The monograph illustrates the richness of inferential goals possible and computational details in fitting these models for a variety of data sets.

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6

Statistical Inference from Genetic Data on Pedigrees

Elizabeth A. Thompson

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This monograph develops probability models and statistical approaches for analysis of genetic data.  The focus is on simple traits, But multiple genetic loci, from basic ideas through recent developments in Monte Carlo Likelihood estimation.

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5

Mixture Models: Theory, Geometry & Applications

Bruce G. Lindsay

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These lecture notes develop a general semi parametric theory for statistical models containing an unknown distribution, with Application in random effects, over dispersion and many more areas. The lectures were originally presented at the NSF-CBMS Regional Conference held at the University of South Carolina, in May 1993.

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4

Higher Order Asymptotics

Jayant K. Ghosh

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These lecture notes are concerned with Edgeworth expansions; higher order efficiency, expansion of posterior, probability matching priors and related topics. These lectures were originally presented at the NSF-CBMS Regional Conference held at Chapel Hill, North Carolina, in August 1991.

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3

Stochastic Curve Estimation

Murray Rosenblatt

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These lecture notes are concerned with probability density or regression function estimation when observations are dependent. The lectures were originally presented at the NSF-CBMS Regional Conference held at the University of California, Davis, in June 1989.

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2

Empirical Processes: Theory & Applications

David Pollard

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These lecture notes present some of the theoretical developments in abstract empirical process theory and illustrate their application by example. The lectures were originally presented at the NSF-CBMS Regional Conference held at the University of Iowa, in July 1988.

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1

Group Invariance Applications in Statistics

Morris L. Eaton

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These lecture notes discuss topics in invariance with application in statistics. These lectures were originally presented at the NSF-CBMS Regional Conference held at the University of Michigan in June 1987.

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