Estimates by bootstrap interval for time series forecasts obtained by theta model
| Autor: | Daniel S. Steffen, Anselmo Chaves Neto |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
021103 operations research
lcsh:Management. Industrial management Series (mathematics) Monte Carlo method Interval estimation 0211 other engineering and technologies Univariate Theta model Time Series 02 engineering and technology 01 natural sciences Bootstrap Term (time) 010104 statistics & probability Forecasting Theta Model lcsh:HD28-70 Resampling Statistics Applied mathematics 0101 mathematics Time series Mathematics |
| Zdroj: | Independent Journal of Management & Production, Vol 8, Iss 1, Pp 144-158 (2017) Independent Journal of Management & Production; Vol. 8 No. 1 (2017): Independent Journal of Management & Production; 144-158 Independent Journal of Management & Production Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) instacron:IJM&P Independent Journal of Management & Production; Vol 8, No 1 (2017): Independent Journal of Management & Production; 144-158 |
| ISSN: | 2236-269X |
| Popis: | In this work, are developed an experimental computer program in Matlab language version 7.1 from the univariate method for time series forecasting called Theta, and implementation of resampling technique known as computer intensive "bootstrap" to estimate the prediction for the point forecast obtained by this method by confidence interval. To solve this problem built up an algorithm that uses Monte Carlo simulation to obtain the interval estimation for forecasts. The Theta model presented in this work was very efficient in M3 Makridakis competition, where tested 3003 series. It is based on the concept of modifying the local curvature of the time series obtained by a coefficient theta (Θ). In it's simplest approach the time series is decomposed into two lines theta representing terms of long term and short term. The prediction is made by combining the forecast obtained by fitting lines obtained with the theta decomposition. The results of Mape's error obtained for the estimates confirm the favorable results to the method of M3 competition being a good alternative for time series forecast. |
| Databáze: | OpenAIRE |
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