The biasness problem of the maximum likelihood estimate (MLE) of the common shape parameter of several Weibull populations is examined in detail. A modified MLE (MMLE) approach is proposed. In the case of complete and Type II censored data, the bias of the MLE can be substantial. This is noticeable even when the sample size is large. Such a bias increases rapidly as the degree of censorship increases and as more populations are involved. The proposed MMLE, however, is nearly unbiased and much more efficient than the MLE, irrespective of the degree of censorship, the sample sizes, and the number of populations involved
Maximum Likelihood Estimation (MLE) is a method of estimating the parameters of a statistical model....
In this paper, two estimation methods(least square estimation and maximum likelihood estimation) wer...
Collaborative targeted maximum likelihood estimation is an extension to targeted maximum likelihood ...
(v0.0 released February 2013) A general method for correcting the bias of the maximum likelihood est...
(v0.0 released February 2013) A general method for correcting the bias of the maximum likelihood est...
The maximum likelihood estimator of the Weibull shape parameter can be very biased. An estimator bas...
The estimation of the common shape parameter across different Weibull populations is an important an...
The inherent bias pathology of the maximum likelihood estimation method is confirmed for models with...
Usually, the parameters of a Weibull distribution are estimated by maximum likelihood estimation. To...
<p>The presence of a nuisance parameter may often perturb the quality of the likelihood-based infere...
For the Weibull distribution the maximum likelihood method does not provide an explicit estimator fo...
Six techniques (maximum likelihood, least squares regression and the Jacquelin, Ross, White and Bain...
none4siThe paper considers the estimation of the parameters of the 2-parameter Weibull distribution ...
Techniques for estimating the parameters of the 2-parameter Weibull distribution from data obtained ...
The technique of unbiasing the maximum likelihood estimates of the scale and shape parameters of the...
Maximum Likelihood Estimation (MLE) is a method of estimating the parameters of a statistical model....
In this paper, two estimation methods(least square estimation and maximum likelihood estimation) wer...
Collaborative targeted maximum likelihood estimation is an extension to targeted maximum likelihood ...
(v0.0 released February 2013) A general method for correcting the bias of the maximum likelihood est...
(v0.0 released February 2013) A general method for correcting the bias of the maximum likelihood est...
The maximum likelihood estimator of the Weibull shape parameter can be very biased. An estimator bas...
The estimation of the common shape parameter across different Weibull populations is an important an...
The inherent bias pathology of the maximum likelihood estimation method is confirmed for models with...
Usually, the parameters of a Weibull distribution are estimated by maximum likelihood estimation. To...
<p>The presence of a nuisance parameter may often perturb the quality of the likelihood-based infere...
For the Weibull distribution the maximum likelihood method does not provide an explicit estimator fo...
Six techniques (maximum likelihood, least squares regression and the Jacquelin, Ross, White and Bain...
none4siThe paper considers the estimation of the parameters of the 2-parameter Weibull distribution ...
Techniques for estimating the parameters of the 2-parameter Weibull distribution from data obtained ...
The technique of unbiasing the maximum likelihood estimates of the scale and shape parameters of the...
Maximum Likelihood Estimation (MLE) is a method of estimating the parameters of a statistical model....
In this paper, two estimation methods(least square estimation and maximum likelihood estimation) wer...
Collaborative targeted maximum likelihood estimation is an extension to targeted maximum likelihood ...