Estimation of the slope parameter for linear regression model with uncertain prior information
Article
Article Title | Estimation of the slope parameter for linear regression model with uncertain prior information |
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ERA Journal ID | 900 |
Article Category | Article |
Authors | Khan, Shahjahan (Author), Hoque, Zahirul (Author) and Saleh, A. K. Md. Ehsanes (Author) |
Journal Title | Journal of Statistical Research |
Journal Citation | 36, pp. 55- 73 |
Number of Pages | 19 |
Year | 2002 |
Publisher | University of Dhaka |
Place of Publication | Dhaka |
ISSN | 0020-3165 |
0256-422X | |
Web Address (URL) | http://jsr.isrt.ac.bd/ |
Abstract | The estimation of the slope parameter of the linear regression model with normal error is considered in this paper when uncertain prior information on the value of the slope is available. Several alternative estimators are de¯ned to incorporate both the sample as well as the non-sample informa- tion in the estimation process. Some important statistical properties of the restricted, preliminary test, and shrinkage estimators are investigated. The performances of the estimators are compared based on the criteria of un- biasedness and mean square error. Both analytical and graphical methods are explored. None of the estimators is found to be uniformly superior over the others. However, if the non-sample information regarding the value of the slope is close to its true value, the shrinkage estimator over performs the rest of the estimators. |
Keywords | Uncertain non-sample prior information; maximumlikelihood, restricted, preliminary test and shrinkage estimators;bias, mean square error and relative efficiency; normal,Student-t, non-central chi-square and F distributions; andincomplete beta ratio. |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 490509. Statistical theory |
Byline Affiliations | Department of Mathematics and Computing |
Carleton University, Canada |
https://research.usq.edu.au/item/9xw85/estimation-of-the-slope-parameter-for-linear-regression-model-with-uncertain-prior-information
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