Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T22:19:29.030Z Has data issue: false hasContentIssue false

Inference on overlap coefficients under the Weibull distribution: Equalshape parameter

Published online by Cambridge University Press:  15 November 2005

Obaid Al-Saidy
Affiliation:
Department of Mathematics and Statistics, Sultan Qaboos University, PO Box 36, P.C. 123 Al-Khod, Sultanate of Oman; obiad@squ.edu.om
Hani M. Samawi
Affiliation:
Department of Statistics, Yarmouk University, Irbid-Jordan 211-63, Jordan; hsamawi@yu.edu.jo; m-saleh@yu.edu.jo
Mohammad F. Al-Saleh
Affiliation:
Department of Statistics, Yarmouk University, Irbid-Jordan 211-63, Jordan; hsamawi@yu.edu.jo; m-saleh@yu.edu.jo
Get access

Abstract

In this paper we consider three measures of overlap, namely Matusia's measure ρ, Morisita's measure λ andWeitzman's measure Δ. These measures are usually used inquantitative ecology and stress-strength models of reliabilityanalysis. Herein we consider two Weibull distributions havingthe same shape parameter and different scale parameters. Thisdistribution is known to be the most flexible life distributionmodel with two parameters. Monte Carlo evaluations are used tostudy the bias and precision of some estimators of these overlapmeasures. Confidence intervals for the measures are alsoconstructed via bootstrap methods and Taylor series approximation.

Type
Research Article
Copyright
© EDP Sciences, SMAI, 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bain, L.J. and Antle, C.E., Estimation of parameters in Weibull the distribution. Technometrics 9 (1967) 621627.
L.J. Bain and M. Engelhardt, Statistical analysis of reliability and life-testing models. Marcel Dekker (1991).
D.B. Brock, T. Wineland, D.H. Freeman, J.H. Lemke and P.A. Scherr, Demographic characteristics, in Established Population for Epidemiologic Studies of the Elderly, Resource Data Book, J. Cornoni- Huntley, D.B. Brock, A.M. Ostfeld, J.O. Taylor and R.B. Wallace Eds. National Institute on Aging, NIH Publication No. 86- 2443. US Government Printing Office, Washington, DC (1986).
Clemons, T.E. and Bradley Jr., A nonparametric measure of the overlapping coefficient. Comp. Statist. Data Analysis 34 (2000) 5161. CrossRef
Cohen, A.C., Multi-censored sampling in three-parameter Weibull distribution. Technometrics 17 (1974) 347352. CrossRef
P.M. Dixon, The Bootstrap and the Jackknife: describing the precision of ecological Indices, in Design and Analysis of Ecological Experiments, S.M. Scheiner and J. Gurevitch Eds. Chapman & Hall, New York (1993) 209–318.
Do, K.N. and Hall, P., On importance resampling for the bootstrap. Biometrika 78 (1991) 161167. CrossRef
Efron, B., Bootstrap methods: another look at the jackknife. Ann. Statist. 7 (1979) 126. CrossRef
W.T. Federer, L.R. Powers and M.G. Payne, Studies on statistical procedures applied to chemical genetic data from sugar beets. Technical Bulletin, Agricultural Experimentation Station, Colorado State University 77 (1963).
P. Hall, On the removal of Skewness by transformation. J. R. Statist. Soc. B 54 (1992) 221–228.
H.L. Harter and A.H. Moore, Asymptotic variances and covariances of maximum-likelihood estimators, from censored samples, of the parameters of the Weibull and gamma populations. Ann. Math. Statist. 38 (1967) 557–570.
Ibrahim, H.I., Evaluating the power of the Mann-Whitney test using the bootstrap method. Commun. Statist. Theory Meth. 20 (1991) 29192931. CrossRef
Ichikawa, M., A meaning of the overlapped area under probability density curves of stress and strength. Reliab. Eng. System Safety 41 (1993) 203204. CrossRef
Inman, H.F. and Bradley, E.L., The Overlapping coefficient as a measure of agreement between probability distributions and point estimation of the overlap of two normal densities. Comm. Statist. Theory Methods 18 (1989) 38513874. CrossRef
F.C. Leone, Y.H. Rutenberg and C.W. Topp, Order statistics and estimators for the Weibull population. Tech. Reps. AFOSR TN 60-489 and AD 237042, Air Force Office of Scientific Research, Washington, DC (1960).
Lieblein, J. and Zelen, M., Statistical investigations of the fatigue life of deep groove ball bearings. Research Paper 2719. J. Res. Natl. Bur Stand. 57 (1956) 273316. CrossRef
Lu, R., Smith, E.P. and Good, I.J., Multivariate measures of similarity and niche overlap. Theoret. Population Ecol. 35 (1989) 121. CrossRef
N. Mann, Point and Interval Estimates for Reliability Parameters when Failure Times have the Two-Parameter Weibull Distribution. Ph.D. dissertation, University of California at Los Angeles, Los Angeles, CA (1965).
N. Mann, Results on location and scale parameters estimation with application to Extreme-Value distribution. Tech. Rep. ARL 670023, Office of Aerospace Research, USAF, Wright-Patterson AFB, OH (1967a).
Mann, N., Tables for obtaining the best linear invariant estimates of parameters of the Weibull distribution. Technometrics 9 (1967b) 629645. CrossRef
Mann, N., Best linear invariant estimation for Weibull distribution. Technometrics 13 (1971) 521533. CrossRef
Matusita, K., Decision rules based on the distance for problem of fir, two samples, and Estimation. Ann. Math. Statist. 26 (1955) 631640. CrossRef
J.I. McCool, Inference on Weibull Percentiles and shape parameter from maximum likelihood estimates. IEEE Trans. Rel. R-19 (1970) 2–9.
S.N. Mishra, A.K. Shah and J.J. Lefante, Overlapping coefficient: the generalized t approach. Commun. Statist. Theory Methods (1986) 15 123–128.
Morisita, M., Measuring interspecific association and similarity between communities. Memoirs of the faculty of Kyushu University. Series E. Biology 3 (1959) 3680.
Mulekar, M.S. and Mishra, S.N., Overlap Coefficient of two normal densities: equal means case. J. Japan Statist. Soc. 24 (1994) 169180.
Mulekar, M.S. and Mishra, S.N., Confidence interval estimation of overlap: equal means case. Comp. Statist. Data Analysis 34 (2000) 121137. CrossRef
D.N.P. Murthy, M. Xie and R. Jiang, Weibull Models. John Wiley & Sons (2004).
Pike, M., A suggested method of analysis of a certain class of experiments in carcinogenesis. Biometrics 29 (1966) 142161. CrossRef
Reser, B. and Faraggi, D., Confidence intervals for the overlapping coefficient: the normal equal variance case. The statistician 48 (1999) 413418.
Rosen, P. and Rammler, B., The laws governing the fineness of powdered coal. J. Inst. Fuels 6 (1933) 2936.
H.M. Samawi, G.G. Woodworth and M.F. Al-Saleh, Two-Sample importance resampling for the bootstrap. Metron (1996) Vol. LIV No. 3–4.
H.M. Samawi, Power estimation for two-sample tests using importance and antithetic r resampling. Biometrical J. 40 (1998) 341–354.
Smith, E.P., Niche breadth, resource availability, and inference. Ecology 63 (1982) 16751681. CrossRefPubMed
Sneath, P.H.A., A method for testing the distinctness of clusters: a test of the disjunction of two clusters in Euclidean space as measured by their overlap. Math. Geol. 9 (1977) 123143. CrossRef
Thoman, D.R., Bain, L.J. and Antle, C.E., Inference on the parameters of the Weibull distribution. Technometrics 11 (1969) 445460. CrossRef
Weibull, W., A statistical theory of the strength of materials. Ing. Vetenskaps Akad. Handl. 151 (1939) 145.
Weibull, W., A statistical distribution function of wide application. J. Appl. Mech. 18 (1951) 293297.
M.S. Weitzman, Measures of overlap of income distributions of white and Negro families in the United States. Technical paper No. 22. Department of Commerce, Bureau of Census, Washington, US (1970).
J.S. White, The moments of log-Weibull Order Statistics. General Motors Research Publication GMR-717. General Motors Corporation, Warren, Michigan (1967).