The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform
Gamze Ozel - One of the best experts on this subject based on the ideXlab platform.
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A new modified Jackknifed Estimator for the Poisson regression model
Journal of Applied Statistics, 2015Co-Authors: Semra Türkan, Gamze OzelAbstract:ABSTRACTThe Poisson regression is very popular in applied researches when analyzing the count data. However, multicollinearity problem arises for the Poisson regression model when the independent variables are highly intercorrelated. Shrinkage Estimator is a commonly applied solution to the general problem caused by multicollinearity. Recently, the ridge regression (RR) Estimators and some methods for estimating the ridge parameter k in the Poisson regression have been proposed. It has been found that some Estimators are better than the commonly used maximum-likelihood (ML) Estimator and some other RR Estimators. In this study, the modified Jackknifed Poisson ridge regression (MJPR) Estimator is proposed to remedy the multicollinearity. A simulation study and a real data example are provided to evaluate the performance of Estimators. Both mean-squared error and the percentage relative error are considered as the performance criteria. The simulation study and the real data example results show that the pro...
Semra Türkan - One of the best experts on this subject based on the ideXlab platform.
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A new modified Jackknifed Estimator for the Poisson regression model
Journal of Applied Statistics, 2015Co-Authors: Semra Türkan, Gamze OzelAbstract:ABSTRACTThe Poisson regression is very popular in applied researches when analyzing the count data. However, multicollinearity problem arises for the Poisson regression model when the independent variables are highly intercorrelated. Shrinkage Estimator is a commonly applied solution to the general problem caused by multicollinearity. Recently, the ridge regression (RR) Estimators and some methods for estimating the ridge parameter k in the Poisson regression have been proposed. It has been found that some Estimators are better than the commonly used maximum-likelihood (ML) Estimator and some other RR Estimators. In this study, the modified Jackknifed Poisson ridge regression (MJPR) Estimator is proposed to remedy the multicollinearity. A simulation study and a real data example are provided to evaluate the performance of Estimators. Both mean-squared error and the percentage relative error are considered as the performance criteria. The simulation study and the real data example results show that the pro...
Yuhe Xia - One of the best experts on this subject based on the ideXlab platform.
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Jackknifed Liu Estimator in linear regression models
Wuhan University Journal of Natural Sciences, 2013Co-Authors: Yuhe XiaAbstract:In this paper, we introduce a generalized Liu Estimator and Jackknifed Liu Estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu Estimator. Under the mean square error(MSE), the Jackknifed Estimator is superior to the Liu Estimator and the Jackknifed ridge Estimator. We also give a method to select the biasing parameter for d. Furthermore, a numerical example is given to illustvate these theoretical results.
Coskun Kus - One of the best experts on this subject based on the ideXlab platform.
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ÝLERLEYEN TÜR TÝP-II SAÐDAN SANSÜRLÜ ÖRNEKLEME DAYALI DÜZGÜN DAÐILIMIN PARAMETRELERÝNÝN JACKKNÝFE TAHMÝN EDÝCÝSÝ
1Co-Authors: Coskun KusAbstract:In this study, Jackknifed Estimators are obtained for the parameters @ and ß of the Uniform(ß ,@) distribution based on progressively type-II right censored sample. Expected values and variances of Jackknifed and non-Jackknifed Estimators are derived and compared. A numerical example is given for using of Estimators.Uniform distribution, progressive type-II right censoring, Jackknifed Estimator, order statistics.