cachexia: Bayesian networks for a cachexia study
In bnmonitor: An Implementation of Sensitivity Analysis in Bayesian Networks

cachexia

R Documentation

Bayesian networks for a cachexia study

Description

Continuous Bayesian networks comparing the dependence of metabolomics for people who suffer and do not suffer of Cachexia

Usage

cachexia_gbn

cachexia_ci

control_gbn

control_ci

cachexia_data

Format

Continuous Bayesian networks over six metabolomics: Adipate (A), Betaine (B), Fumarate (F), Glucose (GC), Glutamine (GM) and Valine (V). The networks cachexia_gbn and cachexia_ci are for people suffering of cachexia and of class GBN and CI respectively. The networks control_gbn and control_ci are for people not suffering of cachexia and of class GBN and CI respectively. The original dataset is stored in cachexia_data.

An object of class GBN of length 3.

An object of class CI of length 4.

An object of class GBN of length 3.

An object of class CI of length 4.

An object of class data.table (inherits from data.frame) with 77 rows and 7 columns.

References

C. Görgen & M. Leonelli (2020), Model-preserving sensitivity analysis for families of Gaussian distributions. Journal of Machine Learning Research, 21: 1-32.

bnmonitor documentation built on Sept. 30, 2024, 9:31 a.m.