Abstract
It is widely recognized that measurement errors often exist in practice and may considerably affect the performance of control charts in some cases. Measurement error variability has uncertainty which may be originated from several sources. Recently, Chakraborty and Khurshid [3] studied the effects of measurement error on control charts for zero-truncated Poisson distribution. In this paper, we study the effect of the two sources of variability on the power characteristics of control charts and obtain the values of average run length (ARL) for the binomial distribution based on the ratio of two Poisson distributions as studied by Sahai and Khurshid [20]. Expression of the power of the control chart under the standardized normal variable for the binomial distribution is also derived when the underlying distribution is the ratio of two Poisson distributions.
© 2013 by Walter de Gruyter Berlin Boston
Articles in the same Issue
- Masthead
- Masthead
- The Kumaraswamy Exponentiated Pareto Distribution
- Sequential Test for Poisson Distribution under Measurement Error
- Measurement Error Effect on the Power of Control Chart for the Ratio of Two Poisson Distributions
- The Bivariate Confluent Hypergeometric Series Distribution and Some of Its Properties
- Availability of a k-out-of-N:F System with Generally Distributed Repair Time and Preventive Maintenance
- Empirical Likelihood Based Control Charts
- Reliable Risk Analysis on the Example of Tsunami Heights
- An Application of EM Test for the Bayesian Change Point Problem
Articles in the same Issue
- Masthead
- Masthead
- The Kumaraswamy Exponentiated Pareto Distribution
- Sequential Test for Poisson Distribution under Measurement Error
- Measurement Error Effect on the Power of Control Chart for the Ratio of Two Poisson Distributions
- The Bivariate Confluent Hypergeometric Series Distribution and Some of Its Properties
- Availability of a k-out-of-N:F System with Generally Distributed Repair Time and Preventive Maintenance
- Empirical Likelihood Based Control Charts
- Reliable Risk Analysis on the Example of Tsunami Heights
- An Application of EM Test for the Bayesian Change Point Problem