Open AccessStepwise Approach in Lagged Variables Time Series Modeling: A Simple Illustration
Author(s) -
Yusma Yanti,
Septian Rahardiantoro
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/621/1/012009
Subject(s) - stepwise regression , variables , regression analysis , statistics , econometrics , mathematics , variable (mathematics) , time series , series (stratigraphy) , goodness of fit , linear regression , simple linear regression , computer science , mathematical analysis , paleontology , biology
Modeling approach in time series data commonly used to forecast the response variable based on the pattern of the predictor variables. The complicated cases occurred when in the model need the lagged variables from these variables. It can increase the number of predictor variables in the model. In this research, the increasing of number of predictor handled by the stepwise method in the regression analysis approach. All possible lag from the variables generated before the stepwise take action to choose the appropriate variables in the model. The illustration in this research based on the advertising-sales relationship of 36 consecutive months. Result of the model can determine the significance predictor variables in the model, and also can give the appropriate goodness of fit criteria for forecasting.