Vol

Title
Authors
/ Editors
Description

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9

Nonparametric Bayesian Inference
Peter Müller and Abel Rodriguez
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Project Euclid
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 ClusterCorrelated Data
Nan Laird, Harvard University
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Project Euclid
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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Project Euclid
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 nonnormally 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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Project Euclid
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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Project Euclid
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 NSFCBMS 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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Project Euclid
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 NSFCBMS 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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Project Euclid
These
lecture notes are concerned with probability density
or regression function estimation when observations
are dependent. The lectures were originally presented
at the NSFCBMS 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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Project Euclid
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 NSFCBMS 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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Project Euclid
These
lecture notes discuss topics in invariance with application
in statistics. These lectures were originally presented
at the NSFCBMS Regional Conference held at the University
of Michigan in June 1987.

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