i-manager Publications

Extreme Value Control Chart for Burr Type XII Distribution

M.S. Ravi Kumar*, R. R. L. Kantam**

* Associate Professor, Department of Community Medicine, Konaseema Institute of Medical Sciences & Research Foundation, Amalapuram, Andhra Pradesh, India.

** Retired Professor, Department of Statistics, Acharya Nagarjuna University, Nagarjunanagar, Andhra Pradesh, India.

Periodicity:October - December'2016
DOI : https://doi.org/10.26634/jmat.5.4.8309

Abstract

Variable control charts are based on subgroup statistics and variation in the values of the subgroup statistics between subgroups. In this paper, sampling distribution of extreme order statistics for a given sample from Burr Type XII Distribution are considered and its percentiles are used to develop an extreme value control chart for a process variate. The approximation to Normal Distribution of the Burr Distribution is explored to develop the technique of popular ANalysis Of Means (ANOM) through Burr Distribution. Comparative study of the approximations are made. The results are explained by an illustration.

Keywords

Burr Type XII Distribution, Extreme Value Control Chart, Extreme Order Statistic, ANOM, Shewart Control Charts.

How to Cite this Article?

Ravikumar, M.S., and Kantam, R.R.L. (2016). Extreme Value Control Chart for Burr Type XII Distribution. i-manager’s Journal on Mathematics, 5(4), 47-51. https://doi.org/10.26634/jmat.5.4.8309

References

[1]. John A. Austin, Jr. (1973). “Control Chart Constants for Largest and Smallest in Sampling from a Normal Distribution using the Generalized Burr Distribution”. Technometrics, Vol.15, No.4, pp.931-933.

[2]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Variable Control Charts in Inverse Gaussian Distribution”. Proceedings of National Conference on Mathematical Sciences and Applications, pp.161-164.

[3]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Time Control Chart – Some IFR Models”. InterStat, pp.1-10.

[4]. Kantam, R.R.L and Ravikumar, M.S. (2013). “Time Control Chart - Burr Distribution”. Collection of Recent Statistical Methods and Applications, A Publication of Department of Statistics, University of Kerala, pp.307-314.

[5]. Kantam, R.R.L., SriRam, B., and Srinivas, V. (2013). “Extreme Value Control Charts in Some Life Testing Models”. International Journal of Scientific and Research Publications, Vol.3, No.9, pp.1-4.

[6]. Montgomery Douglas C. (2001). Introduction to Statistical Quality Control. Third Edition, WSE, pp.213.

[7]. Raid W. Amin and Hans W. Wolff. (2007). “The Behavior of an Extreme - Value Control Charts in the Case of Mixture Alternatives”. The Case of Mixture Alternatives, Sequential Analysis-Design Methods and Applications, Published online (Taylor & Francis Online), pp.35-51.

[8]. Rungsarit Intaramo, and Adisak Pongpullponsak, (2012). “Development of Fuzzy Extreme Value Theory Control Charts Using a -cuts for Skewed Populations”. Applied Mathematical Sciences, Vol.6, No.117, pp.5811-5834.

[9]. Srinivasa Rao, B., Pratapa Reddy, J., and Sarath Babu, G. (2012). “Extreme Value Charts and Analysis of Means (ANOM) Based on the Log Logistic Distribution”. Journal of Modern Applied Statistical Methods, Vol.11, No.2, pp.493-505.

[10]. Srinivasa Rao B. and Kantam, R.R.L. (2012). “Extreme value charts and analysis of means based on half logistic distribution”. International Journal of Quality & Reliability Management, Vol.29, No.5, pp.501-511.

Extreme Value Control Chart for Burr Type XII Distribution

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content:

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25