On least favourable two point priors and minimax estimators under absolute error loss

Metrika ◽  
1993 ◽  
Vol 40 (1) ◽  
pp. 283-298 ◽  
Author(s):  
Wolfgang Bischoff ◽  
Werner Fieger
Keyword(s):  
Absolute Error ◽  
Error Loss ◽  
Minimax Estimators

scholarly journals On predictive density estimation for location families under integrated absolute error loss

Bernoulli ◽  
2017 ◽  
Vol 23 (4B) ◽  
pp. 3197-3212 ◽  
Author(s):  
Tatsuya Kubokawa ◽  
Éric Marchand ◽  
William E. Strawderman
Keyword(s):  
Density Estimation ◽  
Absolute Error ◽  
Predictive Density ◽  
Error Loss

scholarly journals A New Extended Cosine—G Distributions for Lifetime Studies

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2758
Author(s):  
Mustapha Muhammad ◽  
Rashad A. R. Bantan ◽  
Lixia Liu ◽  
Christophe Chesneau ◽  
Muhammad H. Tahir ◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Residual Life ◽  
Series Representation ◽  
Absolute Error ◽  
Quantile Function ◽  
Least Square ◽  
Cumulative Distribution ◽  
Reliability Parameter ◽  
Asymptotic Results ◽  
Error Loss

In this article, we introduce a new extended cosine family of distributions. Some important mathematical and statistical properties are studied, including asymptotic results, a quantile function, series representation of the cumulative distribution and probability density functions, moments, moments of residual life, reliability parameter, and order statistics. Three special members of the family are proposed and discussed, namely, the extended cosine Weibull, extended cosine power, and extended cosine generalized half-logistic distributions. Maximum likelihood, least-square, percentile, and Bayes methods are considered for parameter estimation. Simulation studies are used to assess these methods and show their satisfactory performance. The stress–strength reliability underlying the extended cosine Weibull distribution is discussed. In particular, the stress–strength reliability parameter is estimated via a Bayes method using gamma prior under the square error loss, absolute error loss, maximum a posteriori, general entropy loss, and linear exponential loss functions. In the end, three real applications of the findings are provided for illustration; one of them concerns stress–strength data analyzed by the extended cosine Weibull distribution.

A robust data-driven AVO inversion with logarithm absolute error loss function

2020 ◽  
Vol 68 (2) ◽  
pp. 445-458 ◽  
Author(s):  
Siyuan Du ◽  
Jiashu Zhang ◽  
Guangmin Hu
Keyword(s):  
Loss Function ◽  
Absolute Error ◽  
Data Driven ◽  
Error Loss ◽  
Avo Inversion
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