Yazar "Pescim, Rodrigo R." seçeneğine göre listele

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    The Weibull Marshall-Olkin family: Regression model and application to censored data
    (Taylor & Francis Inc, 2019) Korkmaz, Mustafa Çağatay; Cordeiro, Gauss M.; Yousof, Haitham M.; Pescim, Rodrigo R.; Afify, Ahmed Z.; Nadarajah, Saralee
    We introduce a new class of distributions called the Weibull Marshall-Olkin-G family. We obtain some of its mathematical properties. The special models of this family provide bathtub-shaped, decreasing-increasing, increasing-decreasing-increasing, decreasing-increasing-decreasing, monotone, unimodal and bimodal hazard functions. The maximum likelihood method is adopted for estimating the model parameters. We assess the performance of the maximum likelihood estimators by means of two simulation studies. We also propose a new family of linear regression models for censored and uncensored data. The flexibility and importance of the proposed models are illustrated by means of three real data sets.
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    The xgamma family: Censored regression modelling and applications
    (National Statistical Institute, 2020) Cordeiro, Gauss M.; Altun, Emrah; Korkmaz, Mustafa Çağatay; Pescim, Rodrigo R.; Afify, Ahmed Z.; Yousof, Haitham M.
    In this paper, a new family of distributions with one extra shape parameter, called the xgamma-G, is proposed. comprehensive treatment of some of its mathematical properties including ordinary and incomplete moments and quantile and generating functions are derived. The unknown model parameters are estimated by the maximum likelihood method and the performance of the maximum likelihood estimators are assessed via two extensive simulation studies. Additionally, the log-location-scale regression model for censored data based on a special member of the family is introduced. The usefulness of the proposed models is illustrated utilizing three real data sets.