TY  - BOOK
AU  - Pruscha,Helmut
ED  - SpringerLink (Online service)
TI  - Statistical Analysis of Climate Series: Analyzing, Plotting, Modeling, and Predicting with R 
SN  - 9783642320842
AV  - QA276-280 
U1  - 519.5 23
PY  - 2013///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Statistics
KW  - Climatology
KW  - Atmospheric sciences
KW  - Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
KW  - Statistical Theory and Methods
KW  - Statistics and Computing/Statistics Programs
KW  - Atmospheric Sciences
N1  - 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
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-642-32084-2
ER  -