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Abstract
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This study introduces a generalization of the odd power Cauchy family by adding one more shape parameter to
gain more flexibility modeling the complex data structures. The linear representations for the density, moments, quantile,
and generating functions are derived. The model parameters are estimated employing the maximum likelihood estimation
method. The Monte Carlo simulations are performed under different parameter settings and sample sizes for the proposed
models. In addition, we introduce a new heteroscedastic regression model based on the special member of the proposed
family. Three data sets are analyzed with competitive and proposed models.
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