Free Access
Issue
ESAIM: PS
Volume 9, June 2005
Page(s) 206 - 219
DOI https://doi.org/10.1051/ps:2005010
Published online 15 November 2005
  1. L.J. Bain and C.E. Antle, Estimation of parameters in Weibull the distribution. Technometrics 9 (1967) 621–627. [CrossRef] [MathSciNet] [Google Scholar]
  2. L.J. Bain and M. Engelhardt, Statistical analysis of reliability and life-testing models. Marcel Dekker (1991). [Google Scholar]
  3. 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). [Google Scholar]
  4. T.E. Clemons and Bradley Jr., A nonparametric measure of the overlapping coefficient. Comp. Statist. Data Analysis 34 (2000) 51–61. [CrossRef] [Google Scholar]
  5. A.C. Cohen, Multi-censored sampling in three-parameter Weibull distribution. Technometrics 17 (1974) 347–352. [CrossRef] [Google Scholar]
  6. 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. [Google Scholar]
  7. K.N. Do and P. Hall, On importance resampling for the bootstrap. Biometrika 78 (1991) 161–167. [CrossRef] [MathSciNet] [Google Scholar]
  8. B. Efron, Bootstrap methods: another look at the jackknife. Ann. Statist. 7 (1979) 1–26. [CrossRef] [MathSciNet] [Google Scholar]
  9. 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). [Google Scholar]
  10. P. Hall, On the removal of Skewness by transformation. J. R. Statist. Soc. B 54 (1992) 221–228. [Google Scholar]
  11. 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. [Google Scholar]
  12. H.I. Ibrahim, Evaluating the power of the Mann-Whitney test using the bootstrap method. Commun. Statist. Theory Meth. 20 (1991) 2919–2931. [CrossRef] [Google Scholar]
  13. M. Ichikawa, A meaning of the overlapped area under probability density curves of stress and strength. Reliab. Eng. System Safety 41 (1993) 203–204. [CrossRef] [Google Scholar]
  14. H.F. Inman and E.L. Bradley, 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) 3851–3874. [CrossRef] [MathSciNet] [Google Scholar]
  15. 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). [Google Scholar]
  16. J. Lieblein and M. Zelen, Statistical investigations of the fatigue life of deep groove ball bearings. Research Paper 2719. J. Res. Natl. Bur Stand. 57 (1956) 273–316. [Google Scholar]
  17. R. Lu, E.P. Smith and I.J. Good, Multivariate measures of similarity and niche overlap. Theoret. Population Ecol. 35 (1989) 1–21. [CrossRef] [Google Scholar]
  18. 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). [Google Scholar]
  19. 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). [Google Scholar]
  20. N. Mann, Tables for obtaining the best linear invariant estimates of parameters of the Weibull distribution. Technometrics 9 (1967b) 629–645. [CrossRef] [MathSciNet] [Google Scholar]
  21. N. Mann, Best linear invariant estimation for Weibull distribution. Technometrics 13 (1971) 521–533. [CrossRef] [MathSciNet] [Google Scholar]
  22. K. Matusita, Decision rules based on the distance for problem of fir, two samples, and Estimation. Ann. Math. Statist. 26 (1955) 631–640. [CrossRef] [MathSciNet] [Google Scholar]
  23. J.I. McCool, Inference on Weibull Percentiles and shape parameter from maximum likelihood estimates. IEEE Trans. Rel. R-19 (1970) 2–9. [Google Scholar]
  24. S.N. Mishra, A.K. Shah and J.J. Lefante, Overlapping coefficient: the generalized t approach. Commun. Statist. Theory Methods (1986) 15 123–128. [Google Scholar]
  25. M. Morisita, Measuring interspecific association and similarity between communities. Memoirs of the faculty of Kyushu University. Series E. Biology 3 (1959) 36–80. [Google Scholar]
  26. M.S. Mulekar and S.N. Mishra, Overlap Coefficient of two normal densities: equal means case. J. Japan Statist. Soc. 24 (1994) 169–180. [MathSciNet] [Google Scholar]
  27. M.S. Mulekar and S.N. Mishra, Confidence interval estimation of overlap: equal means case. Comp. Statist. Data Analysis 34 (2000) 121–137. [CrossRef] [Google Scholar]
  28. D.N.P. Murthy, M. Xie and R. Jiang, Weibull Models. John Wiley & Sons (2004). [Google Scholar]
  29. M. Pike, A suggested method of analysis of a certain class of experiments in carcinogenesis. Biometrics 29 (1966) 142–161. [CrossRef] [Google Scholar]
  30. B. Reser and D. Faraggi, Confidence intervals for the overlapping coefficient: the normal equal variance case. The statistician 48 (1999) 413–418. [Google Scholar]
  31. P. Rosen and B. Rammler, The laws governing the fineness of powdered coal. J. Inst. Fuels 6 (1933) 29–36. [Google Scholar]
  32. 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. [Google Scholar]
  33. H.M. Samawi, Power estimation for two-sample tests using importance and antithetic r resampling. Biometrical J. 40 (1998) 341–354. [Google Scholar]
  34. E.P. Smith, Niche breadth, resource availability, and inference. Ecology 63 (1982) 1675–1681. [CrossRef] [Google Scholar]
  35. P.H.A. Sneath, 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) 123–143. [CrossRef] [Google Scholar]
  36. D.R. Thoman, L.J. Bain and C.E. Antle, Inference on the parameters of the Weibull distribution. Technometrics 11 (1969) 445–460. [CrossRef] [MathSciNet] [Google Scholar]
  37. W. Weibull, A statistical theory of the strength of materials. Ing. Vetenskaps Akad. Handl. 151 (1939) 1–45. [Google Scholar]
  38. W. Weibull, A statistical distribution function of wide application. J. Appl. Mech. 18 (1951) 293–297. [Google Scholar]
  39. 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). [Google Scholar]
  40. J.S. White, The moments of log-Weibull Order Statistics. General Motors Research Publication GMR-717. General Motors Corporation, Warren, Michigan (1967). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.