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The Elements of Statistical Learning
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is …
Linear and Generalized Linear Mixed Models and Their Applications
Now in its second edition, this book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and it presents an up-to-date account …
Targeted Learning
The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands …
Partial Identification of Probability Distributions
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has …
Spatial Statistics and Modeling
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers …
Statistical Decision Theory and Bayesian Analysis
In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes …
Theory of Statistics
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory …
Model-based Geostatistics
Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using data obtained at a limited number of spatial locations. The name …
Introduction to Nonparametric Estimation
This is a revised and extended version of the French book. The main changes are in Chapter 1 where the former Section 1. 3 is removed and the rest of the material is substantially …
Partial Identification of Probability Distributions
Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has …