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24 results for “Regression Estimator”
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Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractAN EFFECTIVE TECHNIQUE OF MULTIPLE IMPUTATION IN NONPARAMETRIC QUANTILE REGRESSIONYanan Hu, Qianqian Zhu, Maozai TianIn this study, we consider the nonparametric quantile regression model with the covariates Missing at Random (MAR). Multiple imputation is becoming an increasingly popular approach for analyzing missing data, which combined with quantile regression is not well-developed. We propose an effective and accurate two-stage multiple imputation method for the model based on the quantile regression, which consists of initial imputation … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 4 Jan 2014 · 6,813 accessesView PDFCite
Research ArticleOpen accessIn the abstractSMOOTHING SPLINE IN SEMIPARAMETRIC ADDITIVE REGRESSION MODEL WITH BAYESIAN APPROACHRita Diana, I. Nyoman Budiantara, Purhadi, Satwiko DarmestoSemiparametric additive regression model is a combination of parametric and nonparametric regression models. The parametric components are not linear but following a polynomial pattern, while the nonparametric components are unknown pattern and assumed to be contained in the Sobolev space. The nonparametric components can be approximated by smoothing spline functions. In the development of smoothing spline, the classical statistical approach … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 12 Jun 2013 · 7,252 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Multiresponse Semiparametric Regression ModelSri Haryatmi, I. Nyoman Budiantara, Wahyu WibowoThe modeling between predictors and response in statistics sometimes deals with more than one response or multiresponse situation. Furthermore, it can be happen that some predictors have linear relationship with the responses and the others predictor have unknown relationship. To overcome this modeling problem we proposed multiresponse semiparametric regression model. This model has more than one response and contains both … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 20 Feb 2013 · 7,068 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpline Smoothing for Multi-Response Nonparametric Regression Model in Case of Heteroscedasticity of VarianceBudi Lestari, I. Nyoman Budiantara, Sony Sunaryo, Muhammad MashuriProblem statement: Assume that data (yki, tki), k = 1,2,…, p; i = 1,2,…,nk where nk represents the number of repeated measurement of kth object follows multi-response nonparametric regression model with variances of errors are heteroscedastic. Nonparametric regression curves are unknown and assumed to be smooth which are contained in Sobolev space. Random Errors are independent and normally distributed with … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 13 Oct 2012 · 7,955 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesigning of Child Growth Chart Based on Multi-Response Local Polynomial ModelingNur Chamidah, I. Nyoman Budiantara, Sony Sunaryo, Ismaini ZainProblem 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, … …Journal of Mathematics and Statistics, Vol. 8, Issue 3 · 4 Sep 2012 · 7,506 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Calculating the Hougaard Measure of Skewness in a Nonlinear Regression Model with Two ParametersS. A. EL-ShehawyProblem statement: This study presented an alternative computational algorithm for determining the values of the Hougaard measure of skewness as a nonlinearity measure in a Nonlinear Regression model (NLR-model) with two parameters. Approach: These values indicated a degree of a nonlinear behavior in the estimator of the parameter in a NLR-model. Results: We applied the suggested algorithm on an example … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,159 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Infrastructure Development on Income Generation: A Study on Jamuna Bridge Project in BangladeshShaikh MoniruzzamanThis research is an attempt to examine the impact of infrastructure development on income generation in the north eastern region of Bangladesh which enjoyed a wide range of amenities after the construction of Jamuna Bridge in 1998. The application of 'difference in difference estimator' using the pooled household level income data of the treatment and control area in the pre … …Journal of Social Sciences, Vol. 4, Issue 2 · 30 Jun 2008 · 8,365 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of the Performances of the OLS and some GLS Estimators when Stochastic Regressors are both Collinear and Correlated with Error TermsKayode AyindeThe Classical Linear Regression Model assumes that regressors are non – stochastic, independent and uncorrelated with the error terms. These assumptions are not always tenable especially where regressors are not often assumed fixed in repeated sampling. In this paper, with stochastic regressors, the performances of the Ordinary Least Square (OLS) and some Generalized Least Square (GLS) estimators are investigated and … …Journal of Mathematics and Statistics, Vol. 3, Issue 4 · 31 Dec 2007 · 7,343 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Outlier Detection in Linear RegressionNethal K. Jajo, Xizhi WuNew methodology of robust outlier detection based on Robustly Studentized Robust Residuals (RSRR) examination is well established in linear regression analysis. Two new robust location estimators of linear regression parameters are developed in simple and multiple cases. Based on these robust estimators we obtain RSRR. We used RSRR to derive a new measure of distance to be used in outlier … …American Journal of Applied Sciences, Vol. 1, Issue 2 · 30 Jun 2004 · 6,933 accessesView PDFCite