MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS

Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline...

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Main Authors: Sifriyani Sifriyani, Andrea Tri Rian Dani, Meirinda Fauziyah, Zakiyah Mar’ah
Format: Article
Language:English
Published: Universitas Pattimura 2023-12-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9262
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author Sifriyani Sifriyani
Andrea Tri Rian Dani
Meirinda Fauziyah
Zakiyah Mar’ah
author_facet Sifriyani Sifriyani
Andrea Tri Rian Dani
Meirinda Fauziyah
Zakiyah Mar’ah
author_sort Sifriyani Sifriyani
collection DOAJ
description Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesia
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institution Kabale University
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publishDate 2023-12-01
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spelling doaj-art-9ca63dbd373347759084b86b830195c32025-08-20T03:35:54ZengUniversitas PattimuraBarekeng1978-72272615-30172023-12-011742023203210.30598/barekengvol17iss4pp2023-20329262MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONSSifriyani Sifriyani0Andrea Tri Rian Dani1Meirinda Fauziyah2Zakiyah Mar’ah3Statistics Study Program, Faculty of Mathematics and Natural Sciences, Mulawarman University, IndonesiaStatistics Study Program, Faculty of Mathematics and Natural Sciences, Mulawarman University, IndonesiaStatistics Study Program, Faculty of Mathematics and Natural Sciences, Mulawarman University, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, State Universiy of Makassar, IndonesiaResearch on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesiahttps://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9262espanechnikov kernelhealth sectormixed estimatortruncated spline
spellingShingle Sifriyani Sifriyani
Andrea Tri Rian Dani
Meirinda Fauziyah
Zakiyah Mar’ah
MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
Barekeng
espanechnikov kernel
health sector
mixed estimator
truncated spline
title MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
title_full MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
title_fullStr MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
title_full_unstemmed MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
title_short MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS
title_sort mixed estimators of truncated spline epanechnikov kernel on nonparametric regression and its applications
topic espanechnikov kernel
health sector
mixed estimator
truncated spline
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/9262
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