Book ChapterDOI
Fitting autoregressive models for prediction
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This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models in a stationary time series.Abstract:
This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models. The use of autoregressive representation of a stationary time series (or the innovations approach) in the analysis of time series has recently been attracting attentions of many research workers and it is expected that this time domain approach will give answers to many problems, such as the identification of noisy feedback systems, which could not be solved by the direct application of frequency domain approach [1], [2], [3], [9].read more
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Journal ArticleDOI
Order Choice in Nonlinear Autoregressive Models
TL;DR: The aim of this paper is to present a nonparametric approach that allows to estimate the autoregression order without limiting oneself to any restrictive parametric class of processes.
Book ChapterDOI
Autoregressive Spectral Estimation.
TL;DR: The use of autoregressive spectral densities as exact models and as approximating models for true spectral density is often questioned by skeptical statisticians on the ground that their use in general is ad hoc and without theoretical justification.
Journal ArticleDOI
Bridging AIC and BIC: A New Criterion for Autoregression
TL;DR: In this paper, the authors proposed a new information criterion for order selection for an autoregressive model fitted to time series data, which has the benefits of the two well-known model selection techniques: the Akaike information criterion and the Bayesian information criterion.
Journal ArticleDOI
Climatic trends and periodicities of annual rainfall over India
TL;DR: In this article, the authors studied the trend and periodicities of annual rainfall for 29 sub-divisions of India and all India by using the rainfall series for a period of 124 years (1871-1994).
Journal ArticleDOI
An Empirical Study of the Impact of Internet Financial Reporting on Stock Prices
TL;DR: In this article, the authors examined whether internet financial reporting (IFR) provides information that is quickly reflected in the stock prices, and investigated whether IFR provides financial information that has a significant impact on stock prices.
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