JAMBURA JOURNAL OF PROBABILITY AND STATISTICS
Vol 2, No 2 (2021): Jambura Journal Of Probability and Statistics

ESTIMASI MODEL REGRESI SEMIPARAMETRIK SPLINE TRUNCATED MENGGUNAKAN METODE MAXIMUM LIKELIHOOD ESTIMATION (MLE)

NARITA YURI ADRIANINGSIH (Institut Teknologi Sepuluh Nopember Surabaya)
ANDREA TRI RIAN DANI (Institut Teknologi Sepuluh Nopember Surabaya)



Article Info

Publish Date
20 Oct 2021

Abstract

Regression modeling with a semiparametric approach is a combination of two approaches, namely the parametric regression approach and the nonparametric regression approach. The semiparametric regression model can be used if the response variable has a known relationship pattern with one or more of the predictor variables used, but with the other predictor variables the relationship pattern cannot be known with certainty. The purpose of this research is to examine the estimation form of the semiparametric spline truncated regression model. Suppose that random error is assumed to be independent, identical, and normally distributed with zero mean and variance , then using this assumption, we can estimate the semiparametric spline truncated regression model using the Maximum Likelihood Estimation (MLE) method.  Based on the results, the estimation results of the semiparametric spline truncated regression model were obtained  p=(inv(M'M)) M'y 

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Journal Info

Abbrev

jps

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Social Sciences

Description

Probability Theory Mathematical Statistics Computational Statistics Stochastic Processes Financial Statistics Bayesian Analysis Survival Analysis Time Series Analysis Neural Network Another field which is related to statistics and the applications Another field which is related to Probability and ...