An Efficient Maximum Likelihood Solution in Normal Model having Constant but Unknown Coefficients of Variation
A number of independent normal normal populations having constant but unknown coefficienls of variation are considered. The model is of more general form. There is no restriction on the number of groups and the sample size in each group may differ from one another. An efficient method of solutions...
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1983
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my.upm.eprints.21532013-05-27T06:59:11Z http://psasir.upm.edu.my/id/eprint/2153/ An Efficient Maximum Likelihood Solution in Normal Model having Constant but Unknown Coefficients of Variation Gerig, Thomas M. Abdul Rahman, Mohd Nawi A number of independent normal normal populations having constant but unknown coefficienls of variation are considered. The model is of more general form. There is no restriction on the number of groups and the sample size in each group may differ from one another. An efficient method of solutions based on the maximum likelihood procedure is developed. The maximum likelihood equations are reduced to a single equation. This results in a numerically exact solutions. Monte Carlo evaluations are studied. Examples from the literature are taken to illustrate the method. The estimators for the means are shown to be asymptotically more efficient than the ordinary means. The asymptotic relative efficiency increases as the relative sample size increases. 1983 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/2153/1/An_Efficient_Maximum_Likelihood_Solution_in_Normal_Model.pdf Gerig, Thomas M. and Abdul Rahman, Mohd Nawi (1983) An Efficient Maximum Likelihood Solution in Normal Model having Constant but Unknown Coefficients of Variation. Pertanika, 6 (1). pp. 57-62. English |
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A number of independent normal normal populations having constant but unknown coefficienls
of variation are considered. The model is of more general form. There is no restriction on the number of
groups and the sample size in each group may differ from one another. An efficient method of solutions
based on the maximum likelihood procedure is developed. The maximum likelihood equations are reduced
to a single equation. This results in a numerically exact solutions. Monte Carlo evaluations are studied.
Examples from the literature are taken to illustrate the method. The estimators for the means are shown to
be asymptotically more efficient than the ordinary means. The asymptotic relative efficiency increases as
the relative sample size increases. |
format |
Article |
author |
Gerig, Thomas M. Abdul Rahman, Mohd Nawi |
spellingShingle |
Gerig, Thomas M. Abdul Rahman, Mohd Nawi An Efficient Maximum Likelihood Solution in Normal Model having Constant but Unknown Coefficients of Variation |
author_facet |
Gerig, Thomas M. Abdul Rahman, Mohd Nawi |
author_sort |
Gerig, Thomas M. |
title |
An Efficient Maximum Likelihood Solution in Normal Model
having Constant but Unknown Coefficients of Variation |
title_short |
An Efficient Maximum Likelihood Solution in Normal Model
having Constant but Unknown Coefficients of Variation |
title_full |
An Efficient Maximum Likelihood Solution in Normal Model
having Constant but Unknown Coefficients of Variation |
title_fullStr |
An Efficient Maximum Likelihood Solution in Normal Model
having Constant but Unknown Coefficients of Variation |
title_full_unstemmed |
An Efficient Maximum Likelihood Solution in Normal Model
having Constant but Unknown Coefficients of Variation |
title_sort |
efficient maximum likelihood solution in normal model
having constant but unknown coefficients of variation |
publishDate |
1983 |
url |
http://psasir.upm.edu.my/id/eprint/2153/1/An_Efficient_Maximum_Likelihood_Solution_in_Normal_Model.pdf http://psasir.upm.edu.my/id/eprint/2153/ |
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13.214268 |