An Efficient Method of Parameter and Quantile Estimation for the Three-Parameter Weibull Distribution Based on Statistics Invariant to Unknown Location Parameter

The three-parameter Weibull distribution is widely used in life testing and reliability analysis. In this article, we propose an efficient method for the estimation of parameters and quantiles of the three-parameter Weibull distribution, which avoids the problem of unbounded likelihood, by using statistics invariant to unknown location. Through a Monte Carlo simulation study, we show that the proposed method performs well compared to other prominent methods based on bias and MSE. Finally, we present two illustrative examples.

[1]  Scott D. Brown,et al.  Quantile maximum likelihood estimation of response time distributions , 2002, Psychonomic bulletin & review.

[2]  P. Sen,et al.  Order statistics and inference : estimation methods , 1992 .

[3]  M. Newby,et al.  The Properties of Moment Estimators for the Weibull Distribution Based on the Sample Coeffkient of Variation , 1980 .

[4]  Martin Newby,et al.  Properties of Moment Estimators For the 3-Parameter Weibull Distribution , 1984, IEEE Transactions on Reliability.

[5]  Russell C. H. Cheng,et al.  Corrected Maximum Likelihood in Non‐Regular Problems , 1987 .

[6]  Hon Keung Tony Ng,et al.  Parameter estimation of three-parameter Weibull distribution based on progressively Type-II censored samples , 2012 .

[7]  Masatake Mori,et al.  Double Exponential Formulas for Numerical Integration , 1973 .

[8]  Betty Jones Whitten,et al.  Modified Moment Estimation for the Three-Parameter Weibull Distribution , 1984 .

[9]  G. Cran,et al.  Moment estimators for the 3-parameter Weibull distribution , 1988 .

[10]  Stelios H. Zanakis,et al.  A simulation study of some simple estimators for the three-parameter weibull distribution , 1979 .

[11]  Wayne B. Nelson,et al.  Applied Life Data Analysis: Nelson/Applied Life Data Analysis , 2005 .

[12]  Denis Cousineau,et al.  Nearly unbiased estimators for the three-parameter Weibull distribution with greater efficiency than the iterative likelihood method. , 2009, The British journal of mathematical and statistical psychology.

[13]  J. Bert Keats,et al.  Statistical Methods for Reliability Data , 1999 .

[14]  J. Norris Appendix: probability and measure , 1997 .

[15]  Betty Jones Whitten,et al.  Modified maximum likelihood and modified moment estimators for the three-parameter weibull distribution , 1982 .

[16]  Peter Hall,et al.  Bayesian likelihood methods for estimating the end point of a distribution , 2005 .

[17]  Russell C. H. Cheng,et al.  Estimating Parameters in Continuous Univariate Distributions with a Shifted Origin , 1983 .

[18]  A. Heathcote,et al.  Reply to Speckman and Rouder: A theoretical basis for QML , 2004 .

[19]  Wayne Nelson,et al.  Applied life data analysis , 1983 .

[20]  Necip Doganaksoy,et al.  Weibull Models , 2004, Technometrics.

[21]  Howard E. Rockette,et al.  Maximum Likelihood Estimation with the Weibull Model , 1974 .

[22]  Bhaswati Mukherjee,et al.  Assessing the Value of the Threshold Parameter in the Weibull Distribution Using Bayes Paradigm , 2008, IEEE Transactions on Reliability.

[23]  Lee J. Bain,et al.  Some complete and censored sampling results for the three-parameter weibull distribution , 1980 .

[24]  Russell C. H. Cheng,et al.  Embedded Models in Three-parameter Distributions and their Estimation , 1990 .

[25]  Hideki Nagatsuka,et al.  A consistent method of estimation for the three-parameter Weibull distribution , 2013, Comput. Stat. Data Anal..

[26]  A. Clifford Cohen,et al.  Parameter estimation in reliability and life span models , 1988 .

[27]  Hideo Hirose,et al.  Inference from grouped data in three-parameter Weibull models with applications to breakdown-voltage experiments , 1997 .

[28]  Richard L. Smith Maximum likelihood estimation in a class of nonregular cases , 1985 .

[29]  Bo Ranneby,et al.  The Maximum Spacing Method. An Estimation Method Related to the Maximum Likelihood Method , 2016 .

[30]  Takuji Nishimura,et al.  Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator , 1998, TOMC.

[31]  Gordon Johnston,et al.  Statistical Models and Methods for Lifetime Data , 2003, Technometrics.

[32]  D. Cousineau,et al.  Fitting the three-parameter weibull distribution: review and evaluation of existing and new methods , 2009, IEEE Transactions on Dielectrics and Electrical Insulation.

[33]  Satya D. Dubey,et al.  Some Percentile Estimators for Weibull Parameters , 1967 .

[34]  W. Nelson Statistical Methods for Reliability Data , 1998 .