Point and Interval Estimation for the Burr Type III Distribution

Inference about the Burr Type III Distribution under Type-II Hybrid Censored Data

This paper presents the statistical inference on the parameters of the Burr type III distribution, when the data are Type-II hybrid censored. The maximum likelihood estimators are developed for the unknown parameters using the EM algorithm method. We provided the observed Fisher information matrix using the missing information principle which is useful for constructing the asymptotic confidence...

Interval Estimation For The Scale Parameter Of Burr Type X Distribution Based On Grouped Data

Estimation of the Parameters of Burr Type III Distribution Based on Dual Generalized Order Statistics

The estimation of the parameters of Burr type III distribution based on dual generalized order statistics is considered by using the maximum likelihood (ML) approach as well as the Bayesian approach. The exact expression of the expected Fisher information matrix of the parameters in the distribution is obtained. Also, an approximation based on Lindley is used to obtain the Bayes estimator. To c...

BAYES PREDICTION INTERVALS FOR THE BURR TYPE XI1 DISTRIBUTION IN THE PRESENCE OF OUTLIERS

Using a sample fiom Burr type XU distribution, Bayes prediction intervals are derived for the maximum and minimum of a future sample fromthe same distribution, but in the presence of a single outlier of the type 8,8. The prior of Q is assumed to be the gamma conjugate. A real example is given to illustrate the procedure. Also, the comparison between the values of the prediction bounds for dif...

Point and interval estimation for Gaussian distribution, based on progressively Type-II censored samples

The likelihood equations based on a progressively Type-II censored sample from a Gaussian distribution do not provide explicit solutions in any situation except the complete sample case. This paper examines numerically the bias and mean square error of the MLE, and demonstrates that the probability coverages of the pivotal quantities (for location and scale parameters) based on asymptotic -norm...

Bayes Interval Estimation on the Parameters of the Weibull Distribution for Complete and Censored Tests

A method for constructing confidence intervals on parameters of a continuous probability distribution is developed in this paper. The objective is to present a model for an uncertainty represented by parameters of a probability density function.  As an application, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are derived. The...