Published March 8, 2019
Textbook - 168 Pages - 29 B/W Illustrations
ISBN 9780367146429 - CAT# K412827
Series: Chapman & Hall/CRC Texts in Statistical Science
Introduction
Random field modelling and interpolation
Models and inference for areal unit data
Spatial point processes
Appendix: Solutions to theoretical exercises
Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, real-life examples and theoretical exercises. Solutions to the latter are available in an appendix.
Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers.
* Presents the mathematical foundations of spatial statistics.
* Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology.
* Gives pointers to the literature to facilitate further study.
* Provides example code in R to encourage the student to experiment.
* Offers exercises and their solutions to test and deepen understanding.
The book is suitable for postgraduate and advanced undergraduate students
in mathematics and statistics.
Published April 1, 2019
Textbook - 596 Pages
ISBN 9780367273460 - CAT# K425679
Preface
Chapter 1 Introduction
Chapter 2 Simple Probability Samples
Chapter 3 Stratified Sampling
Chapter 4 Ratio and Regression Estimate
Chapter 5 Cluster Sampling with Equal Probabilities
Chapter 6 Sampling with Unequal Probabilities
Chapter 7 Complex Surveys
Chapter 8 Nonresponse
Chapter 9 Variance Estimation in Complex Surveys
Chapter 10 Categorical Data Analysis in Complex Surveys
Chapter 11 Regression with Complex Survey Data
Chapter 12 Two-Phase Sampling
Chapter 13 Estimating Population Size
Chapter 14 Rare Populations and Small Area Estimation
Chapter 15 Survey Quality
Appendix A Probability Concepts Used in Sampling
References
Author Index
Subject Index
This edition is a reprint of the second edition published by Cengage Learning, Inc. Reprinted with permission.
What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches sampling using real data sets from social sciences, public opinion research, medicine, public health, economics, agriculture, ecology, and other fields.
The book is accessible to students from a wide range of statistical backgrounds. By appropriate choice of sections, it can be used for a graduate class for statistics students or for a class with students from business, sociology, psychology, or biology. Readers should be familiar with concepts from an introductory statistics class including linear regression; optional sections contain the statistical theory, for readers who have studied mathematical statistics.
More than 450 exercises. In each chapter, Introductory Exercises develop skills, Working with Data Exercises give practice with data from surveys, Working with Theory Exercises allow students to investigate statistical properties of estimators, and Projects and Activities Exercises integrate concepts. A solutions manual is available.
Sharon Lohr, the author of Measuring Crime: Behind the Statistics, has published widely about survey sampling and statistical methods for education, public policy, law, and crime. She has been recognized as Fellow of the American Statistical Association, elected member of the International Statistical Institute, and recipient of the Gertrude M. Cox Statistics Award and the Deming Lecturer Award. Formerly Dean’s Distinguished Professor of Statistics at Arizona State University and a Vice President at Westat, she is now a freelance statistical consultant and writer. Visit her website at www.sharonlohr.com.
Published April 16, 2019
Textbook - 275 Pages
ISBN 9780815378648 - CAT# K339002
Series: Chapman & Hall/CRC Texts in Statistical Science
Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures.
In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics:
Advice on selecting prior distributions
Computational methods including Markov chain Monte Carlo (MCMC)
Model-comparison and goodness-of-fit measures, including sensitivity to priors
Frequentist properties of Bayesian methods
Case studies covering advanced topics illustrate the flexibility of the Bayesian approach:
Semiparametric regression
Handling of missing data using predictive distributions
Priors for high-dimensional regression models
Computational techniques for large datasets
Spatial data analysis
The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets, and complete data analyses are available on the book’s website.
Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRoy & Elva Martin Teaching Award.
Sujit K. Ghosh, Professor of Statistics at North Carolina State University, has over 22 years of research and teaching experience in conducting Bayesian analyses, received the Cavell Brownie mentoring award, and served as the Deputy Director at the Statistical and Applied Mathematical Sciences Institute.
July 23, 2019 Forthcoming
Reference - 496 Pages - 10 B/W Illustrations
ISBN 9781138564855 - CAT# K43571
Series: Discrete Mathematics and Its Applications
Combinatorialists are seldom aware of number theoretical tools, and number theorists rarely aware of the possible combinatorial applications. This book is accessible for both of the groups. The first part introduces several important counting sequences and studies their properties in detail. The tools to study these sequences are developed, so very basic preliminary knowledge is necessary. The second part of the book shows how these sequences can be generalized to study new combinatorial problems, and we offer an up to date overview of the present literature. The third part describes the necessary tools to study the number theoretical properties of the counting sequences introduced.
Instructors
I Counting sequences related to set partitions and permutations
Set partitions and permutation cycles.
Generating functions
The Bell polynomials
Unimodality, log concavity and log convexity
The Bernoulli and Cauchy numbers
Ordered partitions
Asymptotics and inequalities
II Generalizations of our counting sequences
Prohibiting elements from being together
Avoidance of big substructures
Prohibiting elements from being together
Avoidance of big substructures
Avoidance of small substructures
III Number theoretical properties
Congurences
Congruences vial finite field methods
Diophantic results
Appendix
To Be Published: 10 May 2019
Publisher: International Press of Boston, Inc.
Hardcover
2078 pages
One of the most eminent of contemporary mathematicians, Shing-Tung Yau has received numerous honors, including the 1982 Fields Medal, considered the highest honor in mathematics, for his work in differential geometry. He is known also for his work in algebraic and Kahler geometry, general relativity, and string theory. His influence in the development and establishment of these areas of research has been great.
These five volumes reproduce a comprehensive selection of his published mathematical papers of the years 1971 to 1991?a period of groundbreaking accomplishments in numerous disciplines including geometric analysis, Kahler geometry, and general relativity.
The editors have organized the contents of this collection by subject area?metric geometry and minimal submanifolds; metric geometry and harmonic functions; eigenvalues and general relativity; and Kahler geometry.
Also presented are expert commentaries on the subject matter, and personal reminiscences that shed light on the development of the ideas which appear in these papers.
This is a set comprising the following volumes, which may be purchased independently:
Selected Works of Shing-Tung Yau 1971-1991: Volume 1
Selected Works of Shing-Tung Yau 1971-1991: Volume 2
l
Selected Works of Shing-Tung Yau 1971-1991: Volume 3
Selected Works of Shing-Tung Yau 1971?1991: Volume 4
Selected Works of Shing-Tung Yau 1971?1991: Volume 5