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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 …
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 …
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 …
Statistical Methods in Software Engineering
This preface pertains to three issues that we would like to bring to the attention of the readers: our objectives, our intended audience, and the nature of the material. We have in …
Statistical Design and Analysis for Intercropping Experiments
Intercropping is an area of research for which there is a desperate need, both in developing countries where people are rapidly depleting scarce resources and still starving, and …
Bayesian Reliability
Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in …
Applied Statistics
This outline of statistics as an aid in decision making will introduce a reader with limited mathematical background to the most important modern statistical methods. This is a …
Semiparametric and Nonparametric Methods in Econometrics
Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random …