000			03037nam a22004937a 4500
001			sulb-eb0024033
003			BD-SySUS
005			20160413122421.0
007			cr nn 008mamaa
008			121030s2013 gw | s |||| 0|eng d
020			_a9783642320842 _9978-3-642-32084-2
024	7		_a10.1007/978-3-642-32084-2 _2doi
050		4	_aQA276-280
072		7	_aPBT _2bicssc
072		7	_aPD _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.5 _223
100	1		_aPruscha, Helmut. _eauthor.
245	1	0	_aStatistical Analysis of Climate Series _h[electronic resource] : _bAnalyzing, Plotting, Modeling, and Predicting with R / _cby Helmut Pruscha.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_aVIII, 176 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aClimate 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.
520			_aThe 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.
650		0	_aStatistics.
650		0	_aClimatology.
650		0	_aAtmospheric sciences.
650	1	4	_aStatistics.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650	2	4	_aClimatology.
650	2	4	_aStatistical Theory and Methods.
650	2	4	_aStatistics and Computing/Statistics Programs.
650	2	4	_aAtmospheric Sciences.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642320835
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-32084-2
912			_aZDB-2-SMA
942			_2Dewey Decimal Classification _ceBooks
999			_c46125 _d46125