Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Parameter: Jurnal Matematika, Statistika dan Terapannya
Jerry Dwi Trijoyo Purnomo
Institut Teknologi Sepuluh Nopember, Indonesia
Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Two-Stage Estimation in Copula-Based Bivariate Survival Models with Cox Marginals Wahyu Dwi Rahmawati; Jerry Dwi Trijoyo Purnomo; Bambang Widjanarko Otok
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp17-28

Abstract

This study is motivated by the presence of dependence between event times in bivariate survival data, which cannot be adequately captured by univariate Cox models. A copula-based bivariate survival model with Cox Proportional Hazards marginals is considered. The estimation procedure follows a two-stage approach, where marginal parameters are first obtained using partial likelihood and the baseline survival function is estimated via the Breslow method. In contrast to conventional approaches that treat marginal estimates as final or imposing shared parameter structures, this study introduces a modification in the second stage by performing simultaneous joint estimation of marginal without imposing shared parameter and dependence parameters using the BHHH algorithm. This allows the marginal parameters to be estimated while explicitly accounting for the dependence between event times. The evaluation was conducted via simulation with variation in sample size, censoring, dependency level and copula types. Simulation results show that the proposed method produces stable and reliable parameter estimates while preserving the interpretability of marginal effects, providing a flexible framework for modeling dependent bivariate survival data.
Parameter Estimation of Partial Spline Regression Using Weighted Least Squares with Moving Average Approach Jiran Julita; Jerry Dwi Trijoyo Purnomo; I Nyoman Budiantara
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp207-2018

Abstract

Regression analysis is a statistical method used to model the relationship between predictor variables and a response variable. In analyzing stunting prevalence, conventional parametric approaches are often limited in capturing complex and nonlinear patterns in the data. Therefore, a semiparametric regression approach is used, as it combines parametric and nonparametric components, providing greater flexibility in modeling relationships between variables. The truncated spline method is applied to accommodate nonlinear patterns, particularly in the variable of access to proper sanitation. This study aims to model the prevalence of stunting in Indonesia using a truncated spline semiparametric regression approach, with the percentage of poor population as the parametric component and access to proper sanitation as the nonparametric component. Parameter estimation is conducted using Ordinary Least Squares (OLS) and improved using Weighted Least Squares (WLS) with a moving average approach to address heteroscedasticity. The optimal model is selected based on the minimum Generalized Cross Validation (GCV) value. The results show that the best model is obtained with order 1 and one knot point at 93.884, producing the minimum GCV value of 25.19599. The WLS approach improves the model performance, increasing the coefficient of determination (R²) from 53.25% to 74.40%, and successfully overcomes heteroscedasticity issues. The analysis also indicates that the percentage of poor population has a positive effect on stunting prevalence, while access to proper sanitation has a negative and nonlinear effect, with a stronger impact after exceeding the knot point. These findings indicate that the truncated spline semiparametric regression model with WLS estimation provides a better and more reliable approach in modeling stunting prevalence.
Co-Authors Bambang Widjanarko Otok I Nyoman Budiantara Jiran Julita Wahyu Dwi Rahmawati