Fr. 117.00

Statistical Analysis of Climate Series - Analyzing, Plotting, Modeling, and Predicting with R

English · Paperback / Softback

Shipping usually within 6 to 7 weeks

Description

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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.

List of contents

Climate series.- Trend and Season.- Correlation: From Yearly to Daily Data.- Model and Prediction: Yearly Data.- Model and Prediction: Monthly Data.- Analysis of Daily Data.- Spectral Analysis.- Complements.- Appendices: A: Excerpt from Climate Data Sets.- B: Some Aspects of Time Series.- C:Categorical Data Analysis- References.- Index.

About the author

Apl. Prof. Dr. Helmut Pruscha wurde 1943 in Teplitz-Schönau geboren. Von 1964 bis 1969 Studium der Mathematik und Physik an den Universitäten Bonn, Freiburg i.Br. und Münschen. 1975 Promotion und 1985 Habilitation im Fach Mathematik an der Universität München. Von 1969 bis 1978 Stipendiat und Assistent am Max-Planck-Institut für Psychiatrie in München. 1975/76 Gastaufenhalt an der Universität Laval (Quebec). Seit 1978 Akademischer Rat und seit 1998 Akademischer Direktor am Mathematischen Institut der Universität München. Mitglied im Sonderforschungsbereich 386, Statistische Analyse diskreter Strukturen.§

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