![](/images/graphics-bg.png)
A Note on the Performance of Biased Estimators with Autocorrelated Errors
Joint Authors
Source
International Journal of Mathematics and Mathematical Sciences
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-30
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
It is a well-established fact in regression analysis that multicollinearity and autocorrelated errors have adverse effects on the properties of the least squares estimator.
Huang and Yang (2015) and Chandra and Tyagi (2016) studied the PCTP estimator and the r-(k,d) class estimator, respectively, to deal with both problems simultaneously and compared their performances with the estimators obtained as their special cases.
However, to the best of our knowledge, the performance of both estimators has not been compared so far.
Hence, this paper is intended to compare the performance of these two estimators under mean squared error (MSE) matrix criterion.
Further, a simulation study is conducted to evaluate superiority of the r-(k,d) class estimator over the PCTP estimator by means of percentage relative efficiency.
Furthermore, two numerical examples have been given to illustrate the performance of the estimators.
American Psychological Association (APA)
Tyagi, Gargi& Chandra, Shalini. 2017. A Note on the Performance of Biased Estimators with Autocorrelated Errors. International Journal of Mathematics and Mathematical Sciences،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1167707
Modern Language Association (MLA)
Tyagi, Gargi& Chandra, Shalini. A Note on the Performance of Biased Estimators with Autocorrelated Errors. International Journal of Mathematics and Mathematical Sciences No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1167707
American Medical Association (AMA)
Tyagi, Gargi& Chandra, Shalini. A Note on the Performance of Biased Estimators with Autocorrelated Errors. International Journal of Mathematics and Mathematical Sciences. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1167707
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1167707