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职业迁徙
个人简介
Hilbe was also a two-time track and field US national champion, and was the University of Hawaii track and field coach in the 1970s and early 1980s. During this period the shot put world record was broken there and the university also produced an NCAA champion in the long jump. In his coaching activities, Hilbe already showed one strength which would forever mark his career and his personal life: an overwhelming dedication to fostering younger generations. Gwen Loud-Johnson (the 1984 NCAA long jump champion), remembers fondly the role Hilbe played in her story: “I came to Hawaii a girl, and left a woman, a wahine… and Joe was like a conductor—he orchestrated it.”
Back in his academic life, Hilbe also made a number of contributions to the fields of count response models and logistic regression. Among his most influential books are two editions of Negative Binomial Regression (Cambridge University Press, 2007, 2011), Modeling Count Data (Cambridge University Press, 2014), and Logistic Regression Models (Chapman & Hall/CRC, 2009). Modeling Count Data won the 2015 PROSE Honorable Mention Award for books in mathematics as the second best mathematics book published in 2014.
Back in his academic life, Hilbe also made a number of contributions to the fields of count response models and logistic regression. Among his most influential books are two editions of Negative Binomial Regression (Cambridge University Press, 2007, 2011), Modeling Count Data (Cambridge University Press, 2014), and Logistic Regression Models (Chapman & Hall/CRC, 2009). Modeling Count Data won the 2015 PROSE Honorable Mention Award for books in mathematics as the second best mathematics book published in 2014.
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论文共 288 篇作者统计合作学者相似作者
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Culture and Education, Cultura y Educaciónno. 3 (2017): 434-460
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BAYESIAN MODELS FOR ASTROPHYSICAL DATA: USING R, JAGS, PYTHON, AND STAN (2017)
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BAYESIAN MODELS FOR ASTROPHYSICAL DATA: USING R, JAGS, PYTHON, AND STANpp.46-67, (2017)
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BAYESIAN MODELS FOR ASTROPHYSICAL DATA: USING R, JAGS, PYTHON, AND STANpp.68-134, (2017)
BAYESIAN MODELS FOR ASTROPHYSICAL DATA: USING R, JAGS, PYTHON, AND STANpp.262-275, (2017)
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openalex(2017)
BAYESIAN MODELS FOR ASTROPHYSICAL DATA: USING R, JAGS, PYTHON, AND STANpp.276-365, (2017)
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Cambridge University Press eBookspp.262-275, (2017)
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作者统计
#Papers: 289
#Citation: 14863
H-Index: 30
G-Index: 119
Sociability: 5
Diversity: 2
Activity: 0
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