Abstract

Problem statements: Anthropometry measures used to measure physical children growth are not onlyweight but also height and head circumference. In this study we develop the estimation of multi-response localpolynomial regression and apply it to design growth chart for children up to five years old based on three responsevariables i.e., weight, height and head circumference. Approach: Based on local polynomial estimator, wedescribe the estimation of multi-response nonparametric regression model by using weighted least squared. Themodel is applied to design health card of children up to five years old by using children data in Surabaya, Indonesia. Generalized Cross Validation (GCV) method is used to determine the order of local polynomial fit and the bandwidthfor each response variable. Results: We formulate the multi-response local polynomial modeling and give a design of health card of children up to five years old in Surabayacity, Indonesia. Conclusion: The child growth chart based on multi-response local polynomial modeling showsincreasing of children nutrition in Surabaya 2010.Because of the strong correlations among all three response variables,the simultaneosly approach for model estimationis better than partly single response approach. The result of simultaneosly model estimation based on multi-response local polynomial modeling satisfies goodness of fit criterion i.e., mean squared error value tend to zero and determination coefficient value tend to one.

Highlights

  • There are many cases that involve the regressionmodel has more than one response variables thatcorrelate each others

  • The local polynomial estimator depends on twoparameters, which must be specified i.e., the order oflocal polynomial fit (d) and the smoothing parameternamed bandwidth (h)

  • In the local polynomial regression, there are twoparameters, i.e., the bandwidth (h) and the order of localpolynomial fit (d) that control the smoothness of thefit and affect the bias-variance trade-off

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Summary

INTRODUCTION

There are many cases that involve the regressionmodel has more than one response variables thatcorrelate each others. The local polynomial estimator depends on twoparameters, which must be specified i.e., the order oflocal polynomial fit (d) and the smoothing parameternamed bandwidth (h). In case of heteroscedasticity, Chamidah (2012) studied estimation of biresponses local polynomialregression model and applied the model to estimategrowth curve of children up to 5 years of age basedon their weight and height. According to pediatrician Roumeliotis (2012) the growthof childrenduring the first 18 months grows rapidly andthen it decreases parallel with increasing of age Roumeliotis (2012) stated anthropometrymeasures which is used to measure physical child growth are weight,height and head circumference of children. We use GCV method andthen apply the model to children growth data inSurabaya, Indonesia 2010. The chart may not appropriate to thecondition of Indonesian children

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