Share

Modern Statistical Methods for Spatial and Multivariate Data

2019-06-29 Mathematics
Download Modern Statistical Methods for Spatial and Multivariate Data PDF Online Free

Author :
Release : 2019-06-29
Genre : Mathematics
Kind : eBook
Book Rating : 317/5 ( reviews)

GET EBOOK


Book Synopsis Modern Statistical Methods for Spatial and Multivariate Data by : Norou Diawara

Download or read book Modern Statistical Methods for Spatial and Multivariate Data written by Norou Diawara. This book was released on 2019-06-29. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.

Modern Statistical Methods for Astronomy

2012-07-12 Science
Download Modern Statistical Methods for Astronomy PDF Online Free

Author :
Release : 2012-07-12
Genre : Science
Kind : eBook
Book Rating : 27X/5 ( reviews)

GET EBOOK


Book Synopsis Modern Statistical Methods for Astronomy by : Eric D. Feigelson

Download or read book Modern Statistical Methods for Astronomy written by Eric D. Feigelson. This book was released on 2012-07-12. Available in PDF, EPUB and Kindle. Book excerpt: Modern Statistical Methods for Astronomy: With R Applications.

Modern Applied Statistics with S

2012-11-05 Mathematics
Download Modern Applied Statistics with S PDF Online Free

Author :
Release : 2012-11-05
Genre : Mathematics
Kind : eBook
Book Rating : 009/5 ( reviews)

GET EBOOK


Book Synopsis Modern Applied Statistics with S by : W.N. Venables

Download or read book Modern Applied Statistics with S written by W.N. Venables. This book was released on 2012-11-05. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modern Applied Statistics with S-PLUS

2013-11-11 Mathematics
Download Modern Applied Statistics with S-PLUS PDF Online Free

Author :
Release : 2013-11-11
Genre : Mathematics
Kind : eBook
Book Rating : 194/5 ( reviews)

GET EBOOK


Book Synopsis Modern Applied Statistics with S-PLUS by : William N. Venables

Download or read book Modern Applied Statistics with S-PLUS written by William N. Venables. This book was released on 2013-11-11. Available in PDF, EPUB and Kindle. Book excerpt: A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.

Statistical Methods for Spatial Data Analysis

2017-01-27 Mathematics
Download Statistical Methods for Spatial Data Analysis PDF Online Free

Author :
Release : 2017-01-27
Genre : Mathematics
Kind : eBook
Book Rating : 477/5 ( reviews)

GET EBOOK


Book Synopsis Statistical Methods for Spatial Data Analysis by : Oliver Schabenberger

Download or read book Statistical Methods for Spatial Data Analysis written by Oliver Schabenberger. This book was released on 2017-01-27. Available in PDF, EPUB and Kindle. Book excerpt: Understanding 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 Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.

You may also like...