Spline Truncated Estimator in Multiresponse Semiparametric Regression Model for Computer based National Exam in West Nusa Tenggara

Lilik Hidayati, Nur Chamidah*, I. Nyoman Budiantara

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

Multiresponse semiparametric regression model is a combination of parametric regression model and nonparametric regression model with response variables more than one and correlate. The estimate used in estimate the parameters is spline truncated. Excess spline truncated is a model that has excellent statistical and visual interpretation and can model data with changing patterns on certain sub-intervals, because spline is a kind of polynomial pieces. The data used in this study is the value of Computer Based National Examination (CBNE) Vocational High School (VHS) in the province of West Nusa Tenggara (NTB) in 2017, each subject tested on CBNE serve as response variables. Based on the significant correlation test results obtained p-value <0.05 so it can be concluded that there is correlation between the responses. The result of the multiresponse semiparametric regression model estimation is obtained by the best model with the value of MSE of 49,608; R2 of 0.84 and minimum GCV value of 0.00000323 so it can be concluded that the value of CBNE VHS in NTB province satisfies goodness of fit criterions.

Original languageEnglish
Article number052029
JournalIOP Conference Series: Materials Science and Engineering
Volume546
Issue number5
DOIs
Publication statusPublished - 1 Jul 2019
Event9th Annual Basic Science International Conference 2019, BaSIC 2019 - Malang, Indonesia
Duration: 20 Mar 201921 Mar 2019

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