Rainfall data modeling using improved adaptive type-II progressively censored Weibull-exponential samples.

To get enough data from experiments that last for a long time, a recently unique improved adaptive Type-II progressive censoring technique has been suggested. This study, taking this scheme into consideration, concentrates on some conventional and Bayesian estimation tasks for parameter and reliability indicators, where the underlying distribution is the Weibull-exponential. From a traditional point of view, the likelihood methodology is explored for gaining point and approximate confidence interval estimates.

Data analysis with applications in physics and engineering using XLindley model with improved adaptive Type-II progressively censored samples.

Recently, a novel improved adaptive Type-II progressive censoring strategy has been suggested in order to obtain adequate data from trials that require a lengthy amount of time. Considering this scheme, this paper focuses on various classical and Bayesian estimation challenges for parameter and some reliability metrics for the XLindley distribution. Two classical estimation methods are considered from the classical perspective to get the point and interval estimations of the model parameter as well as reliability and hazard rate functions.

Estimation procedures and optimal censoring schemes for an improved adaptive progressively type-II censored Weibull distribution.

This paper presents an effort to investigate the estimations of the Weibull distribution using an improved adaptive Type-II progressive censoring scheme. This scheme effectively guarantees that the experimental time will not exceed a pre-fixed time. The point and interval estimations using two classical estimation methods, namely maximum likelihood and maximum product of spacing, are considered to estimate the unknown parameters as well as the reliability and hazard rate functions.

E-Bayesian Estimation Using Spacing Function for Inverse Lindley Adaptive Type-I Progressively Censored Samples: Comparative Study with Applications.

For the first time, this paper offers the Bayesian and E-Bayesian estimation methods using the spacing function (SF) instead of the classical likelihood function. The inverse Lindley distribution, including its parameter and reliability measures, is discussed in this study through the mentioned methods, along with some other classical approaches. Six-point and six-interval estimations based on an adaptive Type-I progressively censored sample are considered.

Inference on Nadarajah-Haghighi distribution with constant stress partially accelerated life tests under progressive type-II censoring.

This paper presents methods of estimation of the parameters and acceleration factor for Nadarajah-Haghighi distribution based on constant-stress partially accelerated life tests. Based on progressive Type-II censoring, Maximum likelihood and Bayes estimates of the model parameters and acceleration factor are established, respectively. In addition, approximate confidence interval are constructed via asymptotic variance and covariance matrix, and Bayesian credible intervals are obtained based on importance sampling procedure.

On estimation procedures of stress-strength reliability for Weibull distribution with application.

For the first time, ten frequentist estimation methods are considered on stress-strength reliability R = P(Y < X) when X and Y are two independent Weibull distributions with the same shape parameter. The start point to estimate the parameter R is the maximum likelihood method. Other than the maximum likelihood method, a nine frequentist estimation methods are used to estimate R, namely: least square, weighted least square, percentile, maximum product of spacing, minimum spacing absolute distance, minimum spacing absolute-log distance, method of Cramér-von Mises, Anderson-Darling and Right-tail Anderson-Darling.

Classical methods of estimation on constant stress accelerated life tests under exponentiated Lindley distribution.

Accelerated life testing is adopted in several fields to obtain adequate failure time data of test units in a much shorter time than testing at normal operating conditions. The lifetime of a product at constant level of stress is assumed to have an exponentiated Lindley distribution. In this paper, besides maximum likelihood method, eight other frequentist methods of estimation, namely, method of least square estimation, method of weighted least square estimation, method of maximum product of spacing estimation, method of minimum spacing absolute distance estimation, method of minimum spacing absolute-log distance estimation, method of Cramér-von-Mises estimation, method of Anderson-Darling estimation and Right-tail Anderson-Darling estimation are considered to estimate the parameters of the exponentiated Lindley distribution under constant stress accelerated life testing.