Ledolter J (1976). ARIMA Models and their Use in Modelling Hydrologic Sequences. IIASA Research Memorandum. IIASA, Laxenburg, Austria: RM-76-069
Download (882kB) | Preview
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.
|Item Type:||Monograph (IIASA Research Memorandum)|
|Research Programs:||System and Decision Sciences - Core (SDS)
Resources and Environment Area (REN)
|Depositing User:||IIASA Import|
|Date Deposited:||15 Jan 2016 01:43|
|Last Modified:||20 Jul 2016 18:47|
Actions (login required)