Inverted Weibull Regression Models and Their Applications

نویسندگان

چکیده

In this paper, we propose the classical and Bayesian regression models for use in conjunction with inverted Weibull (IW) distribution; there are Regression model (IW-Reg) (IW-BReg). proposed models, suggest logarithm identity link functions, while approach, a gamma prior two loss namely zero-one modified general entropy (MGE) functions. To deal outliers apply Huber Tukey’s bisquare (biweight) addition, iteratively reweighted least squares (IRLS) algorithm to estimate coefficients. Further, compare IW-Reg IW-BReg using some performance criteria, such as Akaike’s information criterion (AIC), deviance (D), mean squared error (MSE). Finally, real datasets collected from Saudi Arabia corresponding explanatory variables theoretical findings. The approach shows better terms of considered criteria.

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ژورنال

عنوان ژورنال: Stats

سال: 2021

ISSN: ['2571-905X']

DOI: https://doi.org/10.3390/stats4020019