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- W4287684805 abstract "In this paper, we consider the beta prime regression model recently proposed by cite{bour18}, which is tailored to situations where the response is continuous and restricted to the positive real line with skewed and long tails and the regression structure involves regressors and unknown parameters. We consider two different strategies of bias correction of the maximum-likelihood estimators for the parameters that index the model. In particular, we discuss bias-corrected estimators for the mean and the dispersion parameters of the model. Furthermore, as an alternative to the two analytically bias-corrected estimators discussed, we consider a bias correction mechanism based on the parametric bootstrap. The numerical results show that the bias correction scheme yields nearly unbiased estimates. An example with real data is presented and discussed." @default.
- W4287684805 created "2022-07-26" @default.
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- W4287684805 date "2020-08-26" @default.
- W4287684805 modified "2023-09-26" @default.
- W4287684805 title "Improved estimators in beta prime regression models" @default.
- W4287684805 doi "https://doi.org/10.48550/arxiv.2008.11750" @default.
- W4287684805 hasPublicationYear "2020" @default.
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