By using air-lead data analysed by Krishnamoorthy and Mathew (2009) a Bayesian procedure is applied to obtain control limits for the upper one-sided tolerance limit. Reference and probability matching priors are derived for the pth quantile of a normal distribution. By simulating the predictive density of a future upper one-sided tolerance limit, "run-lengths" and average "run-lengths" are derived. In the second part of this paper control limits are derived for one-sided tolerance limits for the distribution of the difference between two normal random variables. This article illustrates the flexibility and unique features of the Bayesian simulation method for obtaining the posterior predictive distribution of a future one-sided tolerance li...
By extending the results of Human, Chakraborti and Smit (2010), Phase I control charts are derived f...
In Bayesian analysis of clinical trials data, credible intervals are widely used for inference on un...
In probabilistic sensitivity analyses, analysts assign probability distributions to uncertain model ...
A review on statistical tolerance intervals shows that the derivation of two-sided tolerance interva...
We review and contrast frequentist and Bayesian definitions of tolerance regions. We give conditions...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Quality improvement efforts have become the cornerstone of all manufacturing processes. Quality can ...
[[abstract]]A Bayesian nonparametric view of compliance to occupational standards is achieved throug...
This article deals with the construction of an X control chart using the Bayesian perspective. We ob...
Tolerance intervals in a regression setting allow the user to quantify, with a specified degree of c...
This paper introduces a new Bayesian control chart to compare two processes by monitoring the ratio ...
[[abstract]]A method for constructing accurate lower tolerance limits for the balanced one-way norma...
Abstract: Shewhart control limits for individual observations are traditionally based on the average...
The estimation of variance components serves as an integral part of the evaluation of variation, and...
The general objective of the research study underlying this thesis was to develop innovative charts ...
By extending the results of Human, Chakraborti and Smit (2010), Phase I control charts are derived f...
In Bayesian analysis of clinical trials data, credible intervals are widely used for inference on un...
In probabilistic sensitivity analyses, analysts assign probability distributions to uncertain model ...
A review on statistical tolerance intervals shows that the derivation of two-sided tolerance interva...
We review and contrast frequentist and Bayesian definitions of tolerance regions. We give conditions...
The study proposes control limits for X and charts using Bayesian framework assuming the normality o...
Quality improvement efforts have become the cornerstone of all manufacturing processes. Quality can ...
[[abstract]]A Bayesian nonparametric view of compliance to occupational standards is achieved throug...
This article deals with the construction of an X control chart using the Bayesian perspective. We ob...
Tolerance intervals in a regression setting allow the user to quantify, with a specified degree of c...
This paper introduces a new Bayesian control chart to compare two processes by monitoring the ratio ...
[[abstract]]A method for constructing accurate lower tolerance limits for the balanced one-way norma...
Abstract: Shewhart control limits for individual observations are traditionally based on the average...
The estimation of variance components serves as an integral part of the evaluation of variation, and...
The general objective of the research study underlying this thesis was to develop innovative charts ...
By extending the results of Human, Chakraborti and Smit (2010), Phase I control charts are derived f...
In Bayesian analysis of clinical trials data, credible intervals are widely used for inference on un...
In probabilistic sensitivity analyses, analysts assign probability distributions to uncertain model ...