Time Series Analysis: With Applications in R, Second Edition (Springer Texts in Statistics)

✍ Scribed by Jonathan D. Cryer, Kung-Sik Chan

Publisher: Springer
Year: 2008
Tongue: English
Leaves: 500
Series: Springer Texts in Statistics
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.

✦ Table of Contents

front-matter.pdf......Page 1
1_INTRODUCTION.pdf......Page 13
2_FUNDAMENTAL CONCEPTS.pdf......Page 23
3_TRENDS.pdf......Page 39
4_MODELS FOR STATIONARY TIME SERIES.pdf......Page 67
5_MODELS FOR NONSTATIONARY TIME.pdf......Page 98
6_MODEL SPECIFICATION.pdf......Page 119
7_PARAMETER ESTIMATION.pdf......Page 158
8_MODEL DIAGNOSTICS.pdf......Page 184
9_FORECASTING.pdf......Page 200
10_SEASONAL MODELS.pdf......Page 236
11_TIME SERIES REGRESSION MODELS.pdf......Page 258
12_TIME SERIES MODELS OF HETEROSCEDASTICITY.pdf......Page 286
13_INTRODUCTION TO SPECTRAL ANALYSIS.pdf......Page 328
14_ESTIMATING THE SPECTRUM.pdf......Page 360
15_THRESHOLD MODELS.pdf......Page 392
back-matter.pdf......Page 432

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