Title of article
More effective time-series analysis and forecasting
Author/Authors
Anderson، نويسنده , , Oliver D.، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 1995
Pages
31
From page
117
To page
147
Abstract
Our aim is to suggest ways of improving time-domain modelling, for the purpose of more effective forecasting, by better interpretation of the sample autocorrelations and partial autocorrelations obtained from raw time-series data. For this objective, we assume no specialist knowledge, as we start by surveying all those standard ideas of univariate analysis which are needed for the subsequent development of our thesis.
Keywords
Process modelling , ARIMA and ARUMA processes , ARMA , serial correlation , Time domain , Partial autocorrelation , Identifying nonstationarity
Journal title
Journal of Computational and Applied Mathematics
Serial Year
1995
Journal title
Journal of Computational and Applied Mathematics
Record number
1546500
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