TY - JOUR

T1 - Estimation of covariance matrix using multi-response local polynomial estimator for designing children growth charts

T2 - 6th International Conference on Research, Implementation, and Education of Mathematics and Science, ICRIEMS 2019

AU - Chamidah, N.

AU - Lestari, B.

N1 - Funding Information:
Many thanks to Director of the Directorate of Research and Public Service, the Directorate General of Reinforcing of Research and Development, the Ministry of Research, Technology, and Higher Education of the Republic of Indonesia for funding this research via the University Excellence Fundamental Research Grant (Hibah Penelitian Dasar Unggulan Perguruan Tinggi – Hibah PDUPT) in the fiscal year 2019.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.

PY - 2019/12/19

Y1 - 2019/12/19

N2 - In statistical analysis for instance regression analysis we always be faced a estimation problem of regression function which draws relationship between variables in the regression model. In the real cases we frequently meet the relationship between one or more response variables and one or more predictor variables where there are correlations between responses that is called a multi-response regression model. There are two approaches to estimate the multi-response regression model, i.e., parametric and nonparametric. One of estimators in nonparametric regression model is local polynomial estimator for estimating the regression function. Since there are correlations between responses then in the estimating of regression function we need a weight matrix that is to be inverse of covariance matrix of error. Therefore, the main objective of this research is to estimate of covariance matrix of error by using multi-response local polinomial estimator. The result of this research is a covariance matrix estimator that is in the future can be used to design children growth charts.

AB - In statistical analysis for instance regression analysis we always be faced a estimation problem of regression function which draws relationship between variables in the regression model. In the real cases we frequently meet the relationship between one or more response variables and one or more predictor variables where there are correlations between responses that is called a multi-response regression model. There are two approaches to estimate the multi-response regression model, i.e., parametric and nonparametric. One of estimators in nonparametric regression model is local polynomial estimator for estimating the regression function. Since there are correlations between responses then in the estimating of regression function we need a weight matrix that is to be inverse of covariance matrix of error. Therefore, the main objective of this research is to estimate of covariance matrix of error by using multi-response local polinomial estimator. The result of this research is a covariance matrix estimator that is in the future can be used to design children growth charts.

UR - http://www.scopus.com/inward/record.url?scp=85078494539&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1397/1/012072

DO - 10.1088/1742-6596/1397/1/012072

M3 - Conference article

AN - SCOPUS:85078494539

SN - 1742-6588

VL - 1397

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

IS - 1

M1 - 012072

Y2 - 12 July 2019 through 13 July 2019

ER -