Statistical inference about the shape parameter of the Weibull distribution by upper record values

2007 ◽  
Vol 48 (1) ◽  
pp. 95-129 ◽  
Author(s):  
Jong-Wuu Wu ◽  
Hsiao-Chiao Tseng
Keyword(s):  
Weibull Distribution ◽  
Statistical Inference ◽  
Shape Parameter ◽  
Record Values ◽  
Upper Record Values ◽  
Upper Record

Record-Based Estimators for Weibull Distribution

2014 ◽  
Vol 14 (07) ◽  
pp. 1450026 ◽  
Author(s):  
Mahdi Teimouri ◽  
Saralees Nadarajah
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Shape Parameter ◽  
Mean Squared Error ◽  
Likelihood Estimation ◽  
Record Values ◽  
Likelihood Estimator ◽  
Squared Error ◽  
Upper Record Values ◽  
Upper Record

Teimouri and Nadarajah [Statist. Methodol.13 (2013) 12–24] considered bias corrected maximum likelihood estimation of the Weibull distribution based on upper record values. Here, we propose an estimator for the Weibull shape parameter based on consecutive upper records. It is shown by simulations that the proposed estimator has less bias and less mean squared error than an estimator due to Soliman et al. [Comput. Statist. Data Anal.51 (2006) 2065–2077] based on all upper records. Also, the proposed estimator can be considered as a good competitor for the maximum likelihood estimator of the shape parameter based on complete data. This is proved by simulations and using a real dataset.

Inference about Weibull Distribution Using Upper Record Values

2015 ◽  
Vol 22 (04) ◽  
pp. 1550016
Author(s):  
Kai Huang ◽  
Jie Mi
Keyword(s):  
Weibull Distribution ◽  
Prediction Interval ◽  
Record Values ◽  
Testing Procedures ◽  
Scale Parameters ◽  
Upper Record Values ◽  
Record Value ◽  
Upper Record ◽  
Two Parameters ◽  
Two Parameter

This paper studies the frequentist inference about the shape and scale parameters of the two-parameter Weibull distribution using upper record values. The exact sampling distribution of the MLE of the shape parameter is derived. The asymptotic normality of the MLEs of both parameters are obtained. Based on these results this paper proposes various confidence intervals of the two parameters. Assuming one parameter is known certain testing procedures are proposed. Furthermore, approximate prediction interval for the immediately consequent record value is derived too. Conclusions are made based on intensive simulations.

Statistical Inference for the Chen Distribution Based on Upper Record Values

2019 ◽  
Vol 6 (4) ◽  
pp. 831-851 ◽  
Author(s):  
Farhad Yousaf ◽  
Sajid Ali ◽  
Ismail Shah
Keyword(s):  
Statistical Inference ◽  
Record Values ◽  
Upper Record Values ◽  
Upper Record

scholarly journals Upper Record Values from Extended Exponential Distribution

2019 ◽  
Vol 17 (2) ◽  
Author(s):  
Devendra Kumar ◽  
Sanku Dey
Keyword(s):  
Exponential Distribution ◽  
Recurrence Relations ◽  
Shape Parameter ◽  
Record Values ◽  
Exponential Distributions ◽  
Product Moments ◽  
Conditional Moments ◽  
Upper Record Values ◽  
Upper Record

Some recurrence relations are established for the single and product moments of upper record values for the extended exponential distribution by Nadarajah and Haghighi (2011) as an alternative to the gamma, Weibull, and the exponentiated exponential distributions. Recurrence relations for negative moments and quotient moments of upper record values are also obtained. Using relations of single moments and product moments, means, variances, and covariances of upper record values from samples of sizes up to 10 are tabulated for various values of the shape parameter and scale parameter. A characterization of this distribution based on conditional moments of record values is presented.

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