Overview
Within the context of the general climate discussion, the evaluation of climate series gains growing importance ?
Provides application of statistical methods to climatological data Techniques for treating series records
Applying among others ARIMA and GARCH model Programs in R and data sets on climate series are provided at the author's homepage
Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
Keywords
About this book
The book presents the application of statistical methods to climatological data on temperature and precipitation. It provides specific techniques for treating series of yearly, monthly and daily records. The results’ potential relevance in the climate context is discussed.
The methodical tools are taken from time series analysis, from periodogram and wavelet analysis, from correlation and principal component analysis, and from categorical data and event-time analysis.
The applied models are - among others - the ARIMA and GARCH model, and inhomogeneous Poisson processes.
Further, we deal with a number of special statistical topics, e.g. the problem of trend-, season- and autocorrelation-adjustment, and with simultaneous statistical inference.
Programs in R and data sets on climate series, provided at the author’s homepage, enable readers (statisticians, meteorologists, other natural scientists) to perform their own exercises and discover their own applications.
Authors and Affiliations
About the author
Helmut Pruscha, Professor for Mathematics, has served as Academic Director at the University of Munich’s Institute of Mathematics. Before doing so, he had worked for many years as a statistician at a Max-Planck-Institute for neurobiology. His research interests include topics concerning applied statistics and mathematical statistics, especially categorical time series and point processes. He has published several textbooks in German.
Bibliographic Information
Book Title: Statistical Analysis of Climate Series
Book Subtitle: Analyzing, Plotting, Modeling, and Predicting with R
Authors: Helmut Pruscha
DOI: https://doi.org/10.1007/978-3-642-32084-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-32083-5Published: 30 October 2012
Softcover ISBN: 978-3-642-43087-9Published: 09 November 2014
eBook ISBN: 978-3-642-32084-2Published: 30 October 2012
Edition Number: 1
Number of Pages: VIII, 176
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Climatology, Statistical Theory and Methods, Statistics and Computing/Statistics Programs, Atmospheric Sciences