Spatiotemporal data analysis / Gidon Eshel.

Format:

Book

Author/Creator:

Eshel, Gidon, 1958- author.

Language:

English

Subjects (All):

Spatial analysis (Statistics).

Physical Description:

1 online resource (336 p.)

Edition:

Course Book

Place of Publication:

Princeton : Princeton University Press, [2012]

Language Note:

English

System Details:

Mode of access: World Wide Web.

Summary:

"A severe thunderstorm morphs into a tornado that cuts a swath of destruction through Oklahoma. How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China. How do we characterize the spread of the flu, potentially preventing an epidemic? The way to answer important questions like these is to analyze the spatial and temporal characteristics--origin, rates, and frequencies--of these phenomena. This comprehensive text introduces advanced undergraduate students, graduate students, and researchers to the statistical and algebraic methods used to analyze spatiotemporal data in a range of fields, including climate science, geophysics, ecology, astrophysics, and medicine. Gidon Eshel begins with a concise yet detailed primer on linear algebra, providing readers with the mathematical foundations needed for data analysis. He then fully explains the theory and methods for analyzing spatiotemporal data, guiding readers from the basics to the most advanced applications. This self-contained, practical guide to the analysis of multidimensional data sets features a wealth of real-world examples as well as sample homework exercises and suggested exams"-- Provided by publisher.

Contents:

Frontmatter

Contents

Preface

Acknowledgments

Part 1. Foundations

One. Introduction and Motivation

Two. Notation and Basic Operations

Three. Matrix Properties, Fundamental Spaces, Orthogonality

Four. Introduction to Eigenanalysis

Five. The Algebraic Operation of SVD

Part 2. Methods of Data Analysis

Six. The Gray World of Practical Data Analysis: An Introduction to Part 2

Seven. Statistics in Deterministic Sciences: An Introduction

Eight. Autocorrelation

Nine. Regression and Least Squares

Ten. The Fundamental Theorem of Linear Algebra

Eleven. Empirical Orthogonal Functions

Twelve. The SVD Analysis of Two Fields

Thirteen. Suggested Homework

Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781400840632

1400840635

OCLC:

769927219