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Binary regression model using skewed generalized t distributions (기운 일반화 t 분포를 이용한 이진 데이터 회귀 분석)

  • Kim, Mijeong
    • The Korean Journal of Applied Statistics
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    • v.30 no.5
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    • pp.775-791
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    • 2017

  • We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

  • https://doi.org/10.5351/KJAS.2017.30.5.775 인용 PDF KSCI