Bootstrap Confidence Intervals and Parameter Estimation for Zero Inflated Strict Arcsine Model
Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.
[1] H. J. Ader, G. J. Mellenbergh, and D. J. Hand, "Advising on research
methods: A consultant-s companion". Huizen, The Netherlands: Johannes van Kessel Publishing ISBN 978-90-79418-01-5, 2008
[2] J. Carpenter, and J. Bithell, "Bootstrap confidence intervals: when,
which, what? A practical guide for medical guide for medical
statisticians". Statistics in Medicine, 19, 1141-1164, 2000.
[3] A. C. Davison, and D. V. Hinkley, "Bootstrap methods and their application". Cambridge University Press ,1996.
[4] T. J. DiCiccio, and B. Efron, "Bootstrap confidence intervals". Statistical Science, 11, 189-212, 1996.
[5] B. Efron, and R. J. Tibshirani, " An introduction to the Bootstrap".
Chapman and Hall: London, 1993.
[6] A. Gaussiaux, and J. Lemaire, "Methodes d-ajustement de distributions
de sinistres" . Bulletin of the Association of Swiss Actuaries, 81, 87-95, 1981.
[7] W. L. Goffe, G. Ferrier, and J. John Rogers, "Global optimization of
statistical functions with simulated annealing". Journal of Econometric, 60 (1/2), 65-100, 1994
[8] C. C. Kokonenji, "On Strict Arcsine Distribution". Communications in
Statistics. Theory Methods.33(5), 99A3-1006, 2004.
[9] C. C. Kokonendji, and S. Marque, "A strict arcsine regression model".
African Diaspora Journal of Mathematics. Volume 4, Issue 3. Ed by D.
Toka, M. N. Gaston and Z. Said. NOVA Publisher, 2007.
[10] G. Letac, and M. Mora, "Natural real exponential families with cubic
variance functions" . Ann. Statist., 18, 1-37, 1990.
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4th World Conference of the IASC and 6th Conference of the IASC and
6th conference of the Asian Regional Section of the IASC on Computational Statistic and Data Analysis, Yokohama, Japan, 2008.
[12] A. M. Mood, F. A. Graybill, and S. D. Boes, " Introduction to the
Theory of Statistic". McGraw-Hill Series in Probability and Statistics, 1913
[1] H. J. Ader, G. J. Mellenbergh, and D. J. Hand, "Advising on research
methods: A consultant-s companion". Huizen, The Netherlands: Johannes van Kessel Publishing ISBN 978-90-79418-01-5, 2008
[2] J. Carpenter, and J. Bithell, "Bootstrap confidence intervals: when,
which, what? A practical guide for medical guide for medical
statisticians". Statistics in Medicine, 19, 1141-1164, 2000.
[3] A. C. Davison, and D. V. Hinkley, "Bootstrap methods and their application". Cambridge University Press ,1996.
[4] T. J. DiCiccio, and B. Efron, "Bootstrap confidence intervals". Statistical Science, 11, 189-212, 1996.
[5] B. Efron, and R. J. Tibshirani, " An introduction to the Bootstrap".
Chapman and Hall: London, 1993.
[6] A. Gaussiaux, and J. Lemaire, "Methodes d-ajustement de distributions
de sinistres" . Bulletin of the Association of Swiss Actuaries, 81, 87-95, 1981.
[7] W. L. Goffe, G. Ferrier, and J. John Rogers, "Global optimization of
statistical functions with simulated annealing". Journal of Econometric, 60 (1/2), 65-100, 1994
[8] C. C. Kokonenji, "On Strict Arcsine Distribution". Communications in
Statistics. Theory Methods.33(5), 99A3-1006, 2004.
[9] C. C. Kokonendji, and S. Marque, "A strict arcsine regression model".
African Diaspora Journal of Mathematics. Volume 4, Issue 3. Ed by D.
Toka, M. N. Gaston and Z. Said. NOVA Publisher, 2007.
[10] G. Letac, and M. Mora, "Natural real exponential families with cubic
variance functions" . Ann. Statist., 18, 1-37, 1990.
[11] Y. N. Phang, and E. R. Loh. Proceedings: IASC 2008: Joint Meeting of
4th World Conference of the IASC and 6th Conference of the IASC and
6th conference of the Asian Regional Section of the IASC on Computational Statistic and Data Analysis, Yokohama, Japan, 2008.
[12] A. M. Mood, F. A. Graybill, and S. D. Boes, " Introduction to the
Theory of Statistic". McGraw-Hill Series in Probability and Statistics, 1913
@article{"International Journal of Engineering, Mathematical and Physical Sciences:60877", author = "Y. N. Phang and E. F. Loh", title = "Bootstrap Confidence Intervals and Parameter Estimation for Zero Inflated Strict Arcsine Model", abstract = "Zero inflated Strict Arcsine model is a newly developed model which is found to be appropriate in modeling overdispersed count data. In this study, maximum likelihood estimation method is used in estimating the parameters for zero inflated strict arcsine model. Bootstrapping is then employed to compute the confidence intervals for the estimated parameters.
", keywords = "overdispersed count data, maximum likelihood estimation, simulated annealing, BCa confidence intervals.", volume = "6", number = "2", pages = "183-3", }
