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One-Sided Cumulative Sum (CUSUM) Control Charts for the Zero-Truncated Binomial Distribution
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Ashit B. Chakraborty
Veröffentlicht/Copyright:
1. Juni 2011
Abstract
One-sided cumulative sum control charts are constructed for controlling the parameters of a random variable with zero-truncated binomial distribution. It is observed that the Average Run Length (ARL) of the resulting control charts change considerably for a slight shift in the parameters of the distribution under study.
Keywords.: Sequential Probability Ratio Test (SPRT); Cumulative Sum (CUSUM) Control Chart; Average Run Length (ARL); Zero-Truncated Binomial Distribution
Received: 2010-06-15
Published Online: 2011-06-01
Published in Print: 2011-September
© de Gruyter 2011
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Artikel in diesem Heft
- Editorial
- Control Charts Based on the g-and-h Distribution
- Economic Reliability Group Acceptance Sampling Plans Based on the Inverse-Rayleigh and the Log-Logistic Distributions
- Use of Auxiliary Information in Estimating the Finite Population Mean in Survey Sampling
- One-Sided Cumulative Sum (CUSUM) Control Charts for the Zero-Truncated Binomial Distribution
- Significance Test for the Half Logistic Distribution
- The Quality Loss Index QLI and Its Properties
- Statistical Quality Control Limits for the Sample Mean Chart Using Robust Extreme Ranked Set Sampling
Schlagwörter für diesen Artikel
Sequential Probability Ratio Test (SPRT);
Cumulative Sum (CUSUM) Control Chart;
Average Run Length (ARL);
Zero-Truncated Binomial Distribution
Artikel in diesem Heft
- Editorial
- Control Charts Based on the g-and-h Distribution
- Economic Reliability Group Acceptance Sampling Plans Based on the Inverse-Rayleigh and the Log-Logistic Distributions
- Use of Auxiliary Information in Estimating the Finite Population Mean in Survey Sampling
- One-Sided Cumulative Sum (CUSUM) Control Charts for the Zero-Truncated Binomial Distribution
- Significance Test for the Half Logistic Distribution
- The Quality Loss Index QLI and Its Properties
- Statistical Quality Control Limits for the Sample Mean Chart Using Robust Extreme Ranked Set Sampling
