Journal of Statistics: Advances in Theory and ApplicationsAuthor's: Manlika Tanusit
Pages: [45] - [52]
Received Date: August 24, 2009
Submitted by:
The objective of this study is to compare point estimation methods and
interval estimation methods for the Poisson distribution when sample
sizes are small. Three methods of point estimation: Maximum likelihood
method, Bayesian method, and Minimax method, and three methods of
interval estimation: Normal method, Normal-Bayesian method, and
Score-Bayesian method are considered. The lowest mean absolute error
and the lowest average width are used as the criteria to selection for
point estimation and interval estimation, respectively. The scopes of
this study consist of sample sizes: 5, 6, 7, 8, 9, 10, and the
parameter 
equal to 0.02, 0.04, 0.06, 0.08, and 0.1.
Data are simulated 1,000 times generated by using the JAVA software.
The results of this research are as follows. For point estimation, we
recommend that for all sample sizes and parameter 
the Bayesian method should be used. In the
case of interval estimation, Normal-Bayesian method is recommended for
sample sizes 5 to 
between 0.2 to 0.4 and sample sizes 9 to
equal to 0.2, whereas, Score-Bayesian method
should be considered for sample sizes 5 to 8, values of ranging from 0.6 to 1 and sample sizes 9 to
between 0.4 to 1.0.
point estimation methods, interval estimation methods, Poisson distribution.
