Introductory Time Series With R

Author: Paul S.P. Cowpertwait
Publisher: Springer Science & Business Media
ISBN: 0387886982
Size: 13.21 MB
Format: PDF, ePub
View: 2320
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This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation.

Introductory Time Series With R

Author: Paul S.P. Cowpertwait
Publisher: Springer
ISBN: 9780387886978
Size: 25.14 MB
Format: PDF
View: 2815
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This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation.

Time Series Analysis And Its Applications

Author: Robert H. Shumway
Publisher: Springer Science & Business Media
ISBN: 1441978658
Size: 24.15 MB
Format: PDF
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Also new to this edition is the enhanced use of the freeware statistical package R. In particular, R code is now included in the text for nearly all of the numerical examples.

Time Series Analysis

Author: Jonathan D. Cryer
Publisher: Springer Science & Business Media
ISBN: 0387759581
Size: 65.26 MB
Format: PDF, ePub, Mobi
View: 2645
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This book presents an accessible approach to understanding time series models and their applications.

Applied Econometrics With R

Author: Christian Kleiber
Publisher: Springer Science & Business Media
ISBN: 9780387773186
Size: 49.31 MB
Format: PDF
View: 2653
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This is the first book on applied econometrics using the R system for statistical computing and graphics.

Introductory Statistics With R

Author: Peter Dalgaard
Publisher: Springer Science & Business Media
ISBN: 0387790543
Size: 18.63 MB
Format: PDF
View: 3186
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This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics.

Applied Time Series Analysis

Author: Wayne A. Woodward
Publisher: CRC Press
ISBN: 1439897697
Size: 80.77 MB
Format: PDF, ePub, Mobi
View: 550
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The text explores many important new methodologies that have developed in time series, such as ARCH and GARCH processes, time varying frequencies (TVF), wavelets, and more.

Dynamic Linear Models With R

Author: Giovanni Petris
Publisher: Springer Science & Business Media
ISBN: 0387772383
Size: 10.58 MB
Format: PDF
View: 3107
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After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis.