[[abstract]]Wu (2015) proposed the general weighted moments estimators (GWMEs) of the scale parameter of the one-parameter exponential distribution based on a multiply type II censored sample and claimed that the proposed estimator outperforms the other 14 estimators in terms of the exact mean squared errors (MSEs) in most cases. We (2015) used the GWMEs to construct the pivotal quantities to construct the prediction intervals for future observations. In practice, users also want to know the waiting times between two consecutive future observations. Therefore, in this paper we propose the prediction interval for future waiting times or interarrival time. One real life example is given to illustrate the prediction intervals based on GWMEs.[[...
[[abstract]]In this paper, we propose the weighted moments estimators (WMEs) of the scale parameter ...
[[abstract]]In the researching of products' reliability, the result of life testing is used as the b...
Mixed exponential distributions play a significant role in lifetime data analysis, but if we use tra...
We use the general weighted moments estimator (GWME) of the scale parameter of the two-parameter exp...
Wu utilized the general weighted moments estimator (GWMEs) of the scale parameter of the one-paramet...
[[abstract]]In this paper, we make use of an algorithm of Huffer & Lin (2001) in order to develop ex...
[[abstract]]In this paper, we make use of an algorithm of Huffer and Lin (2001) in order to develop ...
[[abstract]]The interval estimation of the scale parameter and the joint confidence region of the pa...
[[abstract]]Exact inference for the location and scale parameters as well as prediction intervals fo...
[[abstract]]The exact inference and prediction intervals for the K-sample exponential scale paramete...
We study the problem of predicting future records based on observed order statistics from two parame...
[[abstract]]The prediction intervals proposed by J. F. Lawless (1971) and G. S. Lingappaiah (1973) f...
Graduation date:1986Prediction intervals for an outcome of a sufficient statistic, T[subscript y], a...
AbstractIn this paper we develop two pivotal quantities to construct exact predication intervals for...
In this paper, the Bayesian prediction intervals (BPI ′s) for a fu-ture observation from generalized...
[[abstract]]In this paper, we propose the weighted moments estimators (WMEs) of the scale parameter ...
[[abstract]]In the researching of products' reliability, the result of life testing is used as the b...
Mixed exponential distributions play a significant role in lifetime data analysis, but if we use tra...
We use the general weighted moments estimator (GWME) of the scale parameter of the two-parameter exp...
Wu utilized the general weighted moments estimator (GWMEs) of the scale parameter of the one-paramet...
[[abstract]]In this paper, we make use of an algorithm of Huffer & Lin (2001) in order to develop ex...
[[abstract]]In this paper, we make use of an algorithm of Huffer and Lin (2001) in order to develop ...
[[abstract]]The interval estimation of the scale parameter and the joint confidence region of the pa...
[[abstract]]Exact inference for the location and scale parameters as well as prediction intervals fo...
[[abstract]]The exact inference and prediction intervals for the K-sample exponential scale paramete...
We study the problem of predicting future records based on observed order statistics from two parame...
[[abstract]]The prediction intervals proposed by J. F. Lawless (1971) and G. S. Lingappaiah (1973) f...
Graduation date:1986Prediction intervals for an outcome of a sufficient statistic, T[subscript y], a...
AbstractIn this paper we develop two pivotal quantities to construct exact predication intervals for...
In this paper, the Bayesian prediction intervals (BPI ′s) for a fu-ture observation from generalized...
[[abstract]]In this paper, we propose the weighted moments estimators (WMEs) of the scale parameter ...
[[abstract]]In the researching of products' reliability, the result of life testing is used as the b...
Mixed exponential distributions play a significant role in lifetime data analysis, but if we use tra...