ARIMA Models and their Use in Modelling Hydrologic Sequences

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/635 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/635 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/635 archive 351 disk0/00/00/06/15 2016-01-15 01:43:38 2021-08-27 17:08:25 2016-01-15 01:43:38 monograph show 2 Ledolter J. AL0225 ARIMA Models and their Use in Modelling Hydrologic Sequences pub iis_mod iis_met iis_wat prog_sds prog_ren In recent years there has been considerable interest in building models which preserve the autocorrelation structure of hydrologic sequences. In particular, Markov models, are frequently entertained to describe the time dependence of run-off sequences. In this paper we follow a more general approach. Instead of restricting ourselves to Markov models, we consider the class of autoregressive integrated moving average (ARIMA) models. This broad class of models is capable of representing many time series observed in practice. Since the distribution of the run-off sequences is frequently skewed, one has to transform the data. In this paper we give some thought to the questions of which transformation one should choose. The class of power transformations is discussed in detail. 1976-09 published RM-76-069 RM-76-069 10 2103 public research_memorandum IIASA, Laxenburg, Austria 45 FALSE info:eu-repo/semantics/book