Microcomputer Applications in Stochastic Hydrologyby Tiao J. Chang, Ohio Univ, Dep of Civil Engineering, Athens, OH, USA,
Abstract: The stochastic precipitation model, namely, Discrete Autoregressive Moving Average (DARMA) process, is used to study daily precipitation time series all over the country. Microsoft Fortran programs are designed to run in an IBM personal computer to compute the autocorrelation function for an initial identification, to estimate the model parameter through nonlinear least squares method, and to select the best model by the minimum variance of the run length distribution. The results show that the seasonal data having strong autocorrelations are inclined to be better fitted by Discrete Autoregressive (DAR) model and those having weak autocorrelations tend to be fitted by Discrete Moving Average (DMA) model.
Subject Headings: Stochastic processes | Computer models | Precipitation | Autoregressive moving average models | Computer software | Data processing | Hydrology | Model analysis
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