Main Article Content
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.
Keywords : Distributed lagged subset model, Prediction, Least square method, Ck Statistic.
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How to Cite
Suparman, S. (2012). Prediction Using Distributed Lagged Subset Model. EKSAKTA: Journal of Sciences and Data Analysis, 12(1). Retrieved from https://jurnal.uii.ac.id/Eksakta/article/view/2440