This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output,…
A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.
This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical…
Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern c…
R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are…
An overview of the theory and application of linear and nonlinear mixed-effects models in the analysis of grouped data, such as longitudinal data, repeated measures, and multilevel data. The authors present a unified model-building strategy for both…
This book is concerned with the processing of signals that have been sam pled and digitized. The fundamental theory behind Digital Signal Process ing has been in existence for decades and has extensive applications to the fields of speech and data c…
This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases, or large in numbers of variables, or large in both. All ideas are illustrated with displays from analyses of real datasets and the importance of in…
Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books
Proven bestseller: almost 6000 copies sold in the U.S. in two editionsNew edition updated to cover S-PLUS 6.0Can be used as an introduction to R, as well as S-PLUSNew exercises have been added; Includes a comparison of S-PLUS and RWell-suited for se…
S-PLUS is a very popular statistical program for statistical researchers and data analysts. The program is available on both UNIX and Windows platforms.
Art, or Science? Which of these is the right way to think of the field of visualization? This is not an easy question to answer, even for those who have many years experience in making graphical depictions of data with a view to help people understa…
Presents a unique foundation for producing almost every quantitative graphic found in scientific journals, newspapers, statistical packages, and data visualization systemsThe new edition features six new chapters and has undergone substantial revisi…
This book systematically addresses the design and analysis of efficient techniques for independent random sampling. Both general-purpose approaches, which can be used to generate samples from arbitrary probability distributions, and tailored techniq…
The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can se…
This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from sur…
Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and mu…
Monte Carlo simulation has become one of the most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. These "pseudorandom" numbers must pass statistical tests just as random s…
Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their…
This book describes an interactive statistical computing environment called 1 XploRe. As the name suggests, support for exploratory statistical analysis is given by a variety of computational tools. XploRe is a matrix-oriented statistical language w…
John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting wi…
Many books teach computational statistics. Until now, however, none has shown how to write a good program. This book gives statisticians, biostatisticians and methodologically-oriented researchers the tools they need to develop high-quality statisti…
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and st…
This book provides clear explanatory text, illustrative mathematics and algorithms, demonstrations of the iterative process, pseudocode, and well-developed examples for applications of the branch-and-bound paradigm to important problems in combinato…
The recent concept of universal (also called automatic or black-box) random variate generation can only be found dispersed in the literature. Being unique in its overall organization, the book covers not only the mathematical and statistical theory…
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in…
S is a high-level language for manipulating, analysing and displayingdata. It forms the basis of two highly acclaimed and widely used dataanalysis software systems, the commercial S-PLUS (R) and the OpenSource R. This book provides an in-depth guide…
Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to exten…
This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate m…
1.1 Overview V ARIOWIN 2.2 is a collection of four Windows (TM) programs - Prevar2D, Vari02D with PCF, Model, and Grid Display - that are used for spatial data analysis and variogram modeling of irregularly spaced data in two dimensions. Prevar2D bu…