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Journal of Applied Statistics Volume 45, 2018 - Issue 11
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Original Articles

Likelihood-based inference for censored linear regression models with scale mixtures of skew-normal distributions

Thalita do Bem MattosDepartment of Statistics, Campinas State University, BrazilView further author information
,
Aldo M. GarayDepartment of Statistics, Federal University of Pernambuco, BrazilCorrespondence[email protected]
[email protected]
View further author information
&
Victor H. LachosDepartment of Statistics, University of Connecticut, Storrs, CT, USAView further author information
Pages 2039-2066 | Received 27 Nov 2016, Accepted 19 Nov 2017, Published online: 02 Dec 2017

Citations (16)

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Read on this site (2)

Amitava Mitra & Pankush Kalgotra. (2022) Optimal trimming proportion in regression analysis for non-normal distributions. Journal of Business Analytics 5:2, pages 152-163.
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Daniel C. F. Guzmán, Clécio S. Ferreira & Camila B. Zeller. (2021) Linear censored regression models with skew scale mixtures of normal distributions. Journal of Applied Statistics 48:16, pages 3060-3085.
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Articles from other publishers (14)

Zakaria Alizadeh Ghajari, Karim Zare & Soheil Shokri. (2024) Estimation in shape mixtures of skew-normal linear regression models via ECM coupled with Gibbs sampling. Monte Carlo Methods and Applications 0:0.
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Sangkon Oh & Byungtae Seo. (2023) Semiparametric mixture of linear regressions with nonparametric Gaussian scale mixture errors. Advances in Data Analysis and Classification 18:1, pages 5-31.
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Jiwon Park, Dipak K. Dey & Víctor H. Lachos. (2024) Finite mixture of regression models for censored data based on the skew-t distribution. Computational Statistics.
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Marcos S Oliveira, Daniela CR Oliveira & Victor H Lachos. (2023) Influence diagnostics for skew- t censored linear regression models . Communications for Statistical Applications and Methods 30:6, pages 605-629.
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Katherine A.L. Valeriano, Christian E. Galarza, Larissa A. Matos & Victor H. Lachos. (2023) Likelihood-based inference for the multivariate skew- regression with censored or missing responses . Journal of Multivariate Analysis 196, pages 105174.
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İsmail Yenilmez & Yeliz Mert Kantar. (2022) New exponentiated generalized censored regression models: Monte Carlo simulation and application. Concurrency and Computation: Practice and Experience 35:1.
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Victor H. Lachos, Jorge L. Bazán, Luis M. Castro & Jiwon Park. (2022) The skew- t censored regression model: parameter estimation via an EM-type algorithm . Communications for Statistical Applications and Methods 29:3, pages 333-351.
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Adelchi Azzalini. (2022) An overview on the progeny of the skew-normal family— A personal perspective. Journal of Multivariate Analysis 188, pages 104851.
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ROGER TOVAR-FALÓN & GUILLERMO MARTÍNEZ-FLÓREZ. (2022) A New Class of Exponentiated Beta-Skew-Laplace Distribution. Anais da Academia Brasileira de Ciências 94:4.
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Christian E. Galarza Morales, Victor H. Lachos & Marcelo Bourguignon. (2021) A skew‐ t quantile regression for censored and missing data . Stat 10:1.
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Sandipan Dutta & Susan Halabi. (2021) A semiparametric modeling approach for analyzing clinical biomarkers restricted to limits of detection. Pharmaceutical Statistics 20:6, pages 1061-1073.
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Elham Mirfarah, Mehrdad Naderi & Ding-Geng Chen. (2021) Mixture of linear experts model for censored data: A novel approach with scale-mixture of normal distributions. Computational Statistics & Data Analysis 158, pages 107182.
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ROGER TOVAR-FALÓN, HELENO BOLFARINE & GUILLERMO MARTÍNEZ-FLÓREZ. (2021) The Asymmetric Power-Student-t Model for Censored and Truncated Data. Anais da Academia Brasileira de Ciências 93:4.
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Roger Tovar-Falón, Heleno Bolfarine & Guillermo Martínez-Flórez. (2020) The Asymmetric Alpha-Power Skew-t Distribution. Symmetry 12:1, pages 82.
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