A Bayesian network interpretation of the Cox's proportional hazard model

DOI10.1016/j.ijar.2018.09.007zbMath1453.62665OpenAlexW2895313814WikidataQ92306294 ScholiaQ92306294MaRDI QIDQ1726284

Jidapa Kraisangka, Marek J. Druzdzel

Publication date: 20 February 2019

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6530916

zbMATH Keywords

Bayesian networkCox's proportional hazard model

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Estimation in survival analysis and censored data (62N02) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Uses Software

• car

Cites Work

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• Probabilistic inference with noisy-threshold models based on a CP tensor decomposition
• Discrete Bayesian Network Interpretation of the Cox’s Proportional Hazards Model
• Learning Parameters in Canonical Models Using Weighted Least Squares
• Nonparametric Estimation from Incomplete Observations
• Efficient computation for the noisy MAX
• Learning Bayesian network parameters from small data sets: Application of Noisy-OR gates

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