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Estimates by bootstrap interval for time series forecasts obtained by theta model

Independent Journal of Management & Production

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Title Estimates by bootstrap interval for time series forecasts obtained by theta model
 
Creator Steffen, Daniel
Chaves Neto, Anselmo
 
Subject —
Forecasting; Time Series; Bootstrap; Theta Model
 
Description 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.
 
Publisher Independent
 
Contributor —
 
Date 2017-03-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
—
 
Format application/pdf
text/html
 
Identifier http://www.ijmp.jor.br/index.php/ijmp/article/view/480
10.14807/ijmp.v8i1.480
 
Source Independent Journal of Management & Production; Vol 8, No 1 (2017): Independent Journal of Management & Production; 144-158
2236-269X
 
Language eng
 
Relation http://www.ijmp.jor.br/index.php/ijmp/article/view/480/623
http://www.ijmp.jor.br/index.php/ijmp/article/view/480/642
http://www.ijmp.jor.br/index.php/ijmp/article/downloadSuppFile/480/242
http://www.ijmp.jor.br/index.php/ijmp/article/downloadSuppFile/480/243
 
Rights Copyright (c) 2017 Daniel Steffen, Anselmo Chaves Neto
http://creativecommons.org/licenses/by/4.0