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Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2015.1024867
Abstract: ABSTRACT In regression analysis, to deal with the problem of multicollinearity, the restricted principal components regression estimator is proposed. In this paper, we compared the restricted principal components regression estimator, the principal components regression estimator,…
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Keywords:
restricted principal;
regression;
regression estimator;
components regression ... See more keywords
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Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2015.1100741
Abstract: ABSTRACT It is well known that the ratio and product estimators have the limitation of having efficiency not exceeding that of the linear regression estimator. This paper develops a new approach to ratio estimation that…
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Keywords:
regression estimator;
efficiency;
estimator;
ratio estimator ... See more keywords
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Published in 2022 at "The Scientific World Journal"
DOI: 10.1155/2022/8171461
Abstract: The mixed Poisson regression models are commonly employed to analyze the overdispersed count data. However, multicollinearity is a common issue when estimating the regression coefficients by using the maximum likelihood estimator (MLE) in such regression…
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Keywords:
regression;
count data;
regression estimator;
estimator ... See more keywords
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Published in 2018 at "Statistics, Optimization and Information Computing"
DOI: 10.19139/soic.v6i3.581
Abstract: Modern statistical analysis often encounters linear models with the number of explanatory variables much larger than the sample size. Estimation in these high-dimensional problems needs some regularization methods to be employed due to rank deficiency…
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Keywords:
high dimensional;
regression;
ridge regression;
estimator ... See more keywords