TY - GEN
T1 - Multiresponse semiparametric regression for modelling the effect of regional socio-economic variables on the use of information technology
AU - Wibowo, Wahyu
AU - Wene, Chatrien
AU - Budiantara, I. Nyoman
AU - Permatasari, Erma Oktania
N1 - Publisher Copyright:
© 2017 Author(s).
PY - 2017/3/27
Y1 - 2017/3/27
N2 - Multiresponse semiparametric regression is simultaneous equation regression model and fusion of parametric and nonparametric model. The regression model comprise several models and each model has two components, parametric and nonparametric. The used model has linear function as parametric and polynomial truncated spline as nonparametric component. The model can handle both linearity and nonlinearity relationship between response and the sets of predictor variables. The aim of this paper is to demonstrate the application of the regression model for modeling of effect of regional socio-economic on use of information technology. More specific, the response variables are percentage of households has access to internet and percentage of households has personal computer. Then, predictor variables are percentage of literacy people, percentage of electrification and percentage of economic growth. Based on identification of the relationship between response and predictor variable, economic growth is treated as nonparametric predictor and the others are parametric predictors. The result shows that the multiresponse semiparametric regression can be applied well as indicate by the high coefficient determination, 90 percent.
AB - Multiresponse semiparametric regression is simultaneous equation regression model and fusion of parametric and nonparametric model. The regression model comprise several models and each model has two components, parametric and nonparametric. The used model has linear function as parametric and polynomial truncated spline as nonparametric component. The model can handle both linearity and nonlinearity relationship between response and the sets of predictor variables. The aim of this paper is to demonstrate the application of the regression model for modeling of effect of regional socio-economic on use of information technology. More specific, the response variables are percentage of households has access to internet and percentage of households has personal computer. Then, predictor variables are percentage of literacy people, percentage of electrification and percentage of economic growth. Based on identification of the relationship between response and predictor variable, economic growth is treated as nonparametric predictor and the others are parametric predictors. The result shows that the multiresponse semiparametric regression can be applied well as indicate by the high coefficient determination, 90 percent.
UR - http://www.scopus.com/inward/record.url?scp=85017591847&partnerID=8YFLogxK
U2 - 10.1063/1.4978994
DO - 10.1063/1.4978994
M3 - Conference contribution
AN - SCOPUS:85017591847
T3 - AIP Conference Proceedings
BT - Symposium on Biomathematics, SYMOMATH 2016
A2 - Benyamin, Beben
A2 - Kasbawati, null
PB - American Institute of Physics Inc.
T2 - 4th International Symposium on Biomathematics, SYMOMATH 2016
Y2 - 7 October 2016 through 9 October 2016
ER -
