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#### Statistical Methods for Spatial Data Analysis

CRC Press 2017; US$ 115.95Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical... more...

#### Multiple Factor Analysis by Example Using R

CRC Press 2016; US$ 89.95Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also... more...

#### Applied Nonparametric Statistical Methods, Fourth Edition

CRC Press 2016; US$ 104.95While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material, this edition begins with a brief summary of some... more...

#### Richly Parameterized Linear Models

CRC Press 2016; US$ 107.00A First Step toward a Unified Theory of Richly Parameterized Linear Models Using mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects. Richly... more...

#### Constrained Principal Component Analysis and Related Techniques

CRC Press 2016; US$ 94.95In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine... more...

#### Nonparametric Statistical Methods Using R

CRC Press 2016; US$ 79.95A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses.... more...

#### Multiple Comparisons Using R

CRC Press 2016; US$ 94.95Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org... more...

#### Data Clustering

CRC Press 2016; US$ 104.95Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data... more...

#### Latent Variable Modeling with R

Taylor and Francis 2015; US$ 51.95This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the... more...

#### R For Dummies

Wiley 2015; US$ 29.99 US$ 26.50Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies , 2 nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this... more...