Evaluating Aging Pedestrian Crash Severity with Bayesian Complementary Log–Log Model for Improved Prediction Accuracy

Producción científica: Article › revisión exhaustiva

Idioma original	English
Páginas (desde-hasta)	155-163
Número de páginas	9
Publicación	Transportation Research Record
Volumen	2659
N.º	1
DOI	https://doi.org/10.3141/2659-17
Estado	Published - 2017

ASJC Scopus Subject Areas

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title = "Evaluating Aging Pedestrian Crash Severity with Bayesian Complementary Log–Log Model for Improved Prediction Accuracy",

author = "Kitali, \{Angela E.\} and Emmanuel Kidando and Thobias Sando and Ren Moses and Ozguven, \{Eren Erman\}",

note = "Publisher Copyright: {\textcopyright} 2017 National Academy of Sciences.",

year = "2017",

doi = "10.3141/2659-17",

language = "English",

volume = "2659",

pages = "155--163",

number = "1",

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T1 - Evaluating Aging Pedestrian Crash Severity with Bayesian Complementary Log–Log Model for Improved Prediction Accuracy

AU - Kitali, Angela E.

AU - Kidando, Emmanuel

AU - Sando, Thobias

AU - Moses, Ren

AU - Ozguven, Eren Erman

PY - 2017

Y1 - 2017

UR - https://www.scopus.com/pages/publications/85049426841

UR - https://www.scopus.com/pages/publications/85049426841#tab=citedBy

U2 - 10.3141/2659-17

DO - 10.3141/2659-17

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SN - 0361-1981

VL - 2659

SP - 155

EP - 163

JO - Transportation Research Record

JF - Transportation Research Record

IS - 1

ER -