Efficient Estimator of Parameters of a Multivariate Geometric Distribution
Corresponding author. Email: ullllhasdixit@yahoo.com.in
- DOI
- 10.2991/jsta.2018.17.4.6How to use a DOI?
- Keywords
- Multivariate geometric distribution; Maximum likelihood estimator; Uniformly minimum variance unbiased estimator; modified MLE
- Abstract
The maximum likelihood estimator (MLE) and uniformly minimum variance unbiased estimator (UMVUE) for the parameters of a multivariate geometric distribution (MGD) have been derived. A modification of the MLE estimator (modified MLE) has been derivedin which case the bias is reduced. The mean square error (MSE) of the modified MLE is less than the MSE of the MLE. Variances of the parameters and the corresponding generalized variance (GV) has been obtained. It has been shown that the MLE and modified MLE are consistent estimators. A comparison of the GVs of modified MLE and UMVUE has shown that the modified MLE is more efficient than the UMVUE. In the final section its application has been discussed with an example of actual data.
- Copyright
- © 2018 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - U. J. Dixit AU - S. Annapurna PY - 2018 DA - 2018/12/31 TI - Efficient Estimator of Parameters of a Multivariate Geometric Distribution JO - Journal of Statistical Theory and Applications SP - 636 EP - 646 VL - 17 IS - 4 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2018.17.4.6 DO - 10.2991/jsta.2018.17.4.6 ID - Dixit2018 ER -