Abstract
We propose a methodology based on control charts when the contaminant concentration follows a Birnbaum-Saunders distribution, which is implemented in the R software. We investigate the performance of this methodology through Monte Carlo simulations. An example with real-world data is given as an illustration of the proposed methodology.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aarset, M.V.: How to identify a bathtub hazard rate. IEEE Trans. Reliab. 36, 106–108 (1987)
Azevedo, C., Leiva, V., Athayde, E., Balakrishnan, N.: Shape and change point analyses of the Birnbaum-Saunders-\(t\) hazard rate and associated estimation. Comput. Stat. Data Anal. 56, 3887–3897 (2012)
Balakrishnan, N., Leiva, V., López, J.: Acceptance sampling plans from truncated life tests from generalized Birnbaum-Saunders distribution. Commun. Stat. Simul. Comput. 36, 643–656 (2007)
Barros, M., Paula, G.A., Leiva, V.: An R implementation for generalized Birnbaum-Saunders distributions. Comput. Stat. Data Anal. 53, 1511–1528 (2009)
Barros, M., Leiva, V., Ospina, R., Tsuyuguchi, A.: Goodness-of-fit tests for the Birnbaum-Saunders distribution with censored reliability data. IEEE Trans. Reliab. 63, 543–554 (2014)
Bhatti, C.R.: The Birnbaum-Saunders autoregressive conditional duration model. Math. Comput. Simul. 80, 2062–2078 (2010)
Box, G.E., Cox, D.R.: An analysis of transformations. J. R. Stat. Soc. B 26, 211–246 (1964)
Ferreira, M., Gomes, M.I., Leiva, V.: On an extreme value version of the Birnbaum-Saunders distribution. Revstat Stat. J. 10, 181–210 (2012)
Fierro, R., Leiva, V., Ruggeri, F., Sanhueza, A.: On a Birnbaum-Saunders distribution arising from a non-homogeneous Poisson process. Stat. Probab. Lett. 83, 1233–1239 (2013)
Figueiredo, F., Gomes, M.I.: The skew-normal distribution in SPC. Revstat Stat. J. 11, 83–104 (2013)
Grigg, O.A., Farewell, V.T.: A risk-adjusted sets method for monitoring adverse medical outcomes. Stat. Med. 23, 1593–1602 (2004)
Huang, S., Qu, Y.: The loss in power when the test of differential expression is performed under a wrong scale. J. Comput. Biol. 13, 786–797 (2006)
Johnson, N.L., Kotz, S., Balakrishnan, N.: Continuous Univariate Distributions. Wiley, New York (1995)
Kelmansky, D., Martinez, E., Leiva, V.: A new variance stabilizing transformation for gene expression data analysis. Stat. Appl. Genet. Mol. Biol. 12, 653–666 (2013)
Kundu, D., Kannan, N., Balakrishnan, N.: On the hazard function of Birnbaum-Saunders distribution and associated inference. Comput. Stat. Data Anal. 52, 2692–2702 (2008)
Leiva, V., Barros, M., Paula, G.A., Sanhueza, A.: Generalized Birnbaum-Saunders distributions applied to air pollutant concentration. Environmetrics 19, 235–249 (2008)
Leiva, V., Sanhueza, A., Angulo, J.M.: A length-biased version of the Birnbaum-Saunders distribution with application in water quality. Stoch. Environ. Res. Risk Assess. 23, 299–307 (2009)
Leiva, V., Sanhueza, A., Kelmansky, S., Martinez, E.: On the glog-normal distribution and its association with the gene expression problem. Comput. Stat. Data Anal. 53, 1613–1621 (2009)
Leiva, V., Vilca, F., Balakrishnan, N., Sanhueza, A.: A skewed sinh-normal distribution and its properties and application to air pollution. Commun. Stat. Theory Method 39, 426–443 (2010)
Leiva, V., Marchant, C., Saulo, H., Aslam, M., Rojas, F.: Capability indices for Birnbaum-Saunders processes applied to electronic and food industries. J. Appl. Stat. 41, 1881–1902 (2014)
Leiva, V., Saulo, H., Leao, J., Marchant, C.: A family of autoregressive conditional duration models applied to financial data. Comput. Stat. Data Anal. 79, 175–191 (2014)
Lio, Y.L., Park, C.: A bootstrap control chart for Birnbaum-Saunders percentiles. Qual. Reliab. Eng. Int. 24, 585–600 (2008)
Lio, Y.L., Tsai, T.R., Wu, S.J.: Acceptance sampling plans from truncated life tests based on the Birnbaum-Saunders distribution for percentiles. Commun. Stat. Simul. Comput. 39, 1–18 (2008)
Manly, B.F.J.: Statistics for Environmental Science and Management. Chapman & Hall, Boca Raton (2009)
Marchant, C., Leiva, V., Cavieres, M.F., Sanhueza, A.: Air contaminant statistical distributions with application to PM10 in Santiago, Chile. Rev. Environ. Contam. Toxicol. 223, 1–31 (2013)
Morrison, L.W.: The use of control charts to interpret environmental monitoring data. Nat. Areas J. 28, 66–73 (2008)
Montgomery, D.: Introduction to Statical Quality Control. Wiley, New York (2008)
Ng, H.K.T., Kundu, D., Balakrishnan, N.: Modified moment estimation for the two-parameter Birnbaum-Saunders distribution. Comput. Stat. Data Anal. 43, 283–298 (2003)
Ott, W.R.: A physical explanation of the lognormality of pollution concentrations. J. Air Waste Manag. Assoc. 40, 1378–1383 (1990)
Raaijmakers, F.J.M.: The lifetime of a standby system of units having the Birnbaum-Saunders distribution. J. Appl. Probab. 17, 490–497 (1980)
Raaijmakers, F.J.M.: Reliability of standby system for units with the Birnbaum-Saunders distribution. IEEE Trans. Reliab. 30, 198–199 (1981)
Saulo, H., Leiva, V., Ziegelmann, F.A., Marchant, C.: A nonparametric method for estimating asymmetric densities based on skewed Birnbaum-Saunders distributions applied to environmental data. Stoch. Environ. Res. Risk Assess. 27, 1479–1491 (2013)
Vilca, F., Sanhueza, A., Leiva, V., Christakos, G.: An extended Birnbaum-Saunders model and its application in the study of environmental quality in Santiago, Chile. Stoch. Environ. Res. Risk Assess. 24, 771–782 (2010)
Vilca, F., Santana, L., Leiva, V., Balakrishnan, N.: Estimation of extreme percentiles in Birnbaum-Saunders distributions. Comput. Stat. Data Anal. 55, 1665–1678 (2011)
Woodall, W.H.: The use of control charts in health-care and public-health surveillance. J. Qual. Tech. 38, 89–104 (2006)
Acknowledgments
The authors wish to thank the Editors of the volume “Risk Assessment Challenges: Theory and Practice” of Springer Proceedings in Mathematics and Statistics, Dr. Christos Kitsos and Dr. Teresa A. Oliveira, and three anonymous referees for their constructive comments on an earlier version of this manuscript which resulted in this improved version. This research was partially supported by FONDECYT 1120879 grant from Chile, and by CAPES, CNPq and FACEPE grants from Brazil. H. Saulo thanks Universidade Federal de Goiás from Brazil for supporting this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Saulo, H., Leiva, V., Ruggeri, F. (2015). Monitoring Environmental Risk by a Methodology Based on Control Charts. In: Kitsos, C., Oliveira, T., Rigas, A., Gulati, S. (eds) Theory and Practice of Risk Assessment. Springer Proceedings in Mathematics & Statistics, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-319-18029-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-18029-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18028-1
Online ISBN: 978-3-319-18029-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)