EKSAKTA: Journal of Sciences and Data Analysis
VOLUME 12, ISSUE 1, February 2011

Prediction Using Distributed Lagged Subset Model

Suparman Suparman (Unknown)



Article Info

Publish Date
15 Feb 2012

Abstract

This  article  examines  the  problem  of  determining  the  future  value  of  the  dependent variable in the distributed lagged subset model. Unlike a distributed lag model in general, which assumes that all coefficients are not zero. In a distributed lagged subset model, some coefficients may be zero. The purpose of  this  study was  to determine  the predictive value of  the dependent variable in a distributed lagged subset model. The approach used to estimate the parameters of a distributed lagged subset model is the least square method and Ck statistic. Least squares method is used to determine the estimators of the coefficient of a distributed lagged subset model. Ck Statistic is used to select the best distributed lagged subset model. Some  simulations are delivered and prove  the efficiency of  this approach. Furthermore, this approach is implemented in real economic data.  Keywords : Distributed lagged subset model, Prediction, Least square method, Ck Statistic.  

Copyrights © 2011






Journal Info

Abbrev

eksakta

Publisher

Subject

Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

Description

Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential ...