Olatayo, T.O. and Akomolafe, A.A. and Adeboye, N.O. (2014) On Boostrap Prediction Intervals for Autoregressive Model. Australian Journal of Basic and Applied Sciences, 8 (6). pp. 385-389. ISSN 1991- 8178
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Abstract
Background:Frequently, an estimated mean squared error is the only indicator or yardstick of measuring error in a prediction. However, the statement that the future values falls in an interval with a specified probability is more informative. Prediction intervals have this probabilistic interpretation, which is similar to that of tolerance intervals . Two resampling methods yield prediction intervals that obtain some types of asymptotic invariance to the sampling distribution. The resampling procedure proposed here utilizes the bootstrap method. The bootstrap interval derives from an empirical distribution generated using bootstrap resampling. The bootstrap is a resampling technique whose aim is to gain information on the distribution of an estimator. Objective: The bootstrap method for measures of Statistical accuracy such as standard error, bias, prediction error and to complicated data structures such as autoregressive models are considered. We estimated the parameters and the bootstrap t confidence interval with an autoregressive model fitted to the real data. Results:Bootstrap prediction intervals provide a non parametric measure of the probable error of forecast from a standard linear autoregressive model. Empirical measure prediction error rate motivate the choice of these intervals, which are calculated by an application of the bootstrap methods, to a time series data. Conclution: Bootstrap prediction intervals represent a useful addition to the traditional set of measures to assess the accuracy of forecast. The asymptotic properties of the intervals do not depend upon the sampling distribution, and the bootstrap results suggest that the invariance approximately holds for relatively all sample sizes.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Chemistry |
| Depositing User: | Mr Taiwo Egbeyemi |
| Date Deposited: | 10 Jul 2020 10:45 |
| Last Modified: | 10 Jul 2020 10:45 |
| URI: | http://eprints.federalpolyilaro.edu.ng/id/eprint/976 |
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