coronary: Coronary heart disease data set
In bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

coronary

R Documentation

Coronary heart disease data set

Description

Probable risk factors for coronary thrombosis, comprising data from 1841 men.

Usage

data(coronary)

Format

The coronary data set contains the following 6 variables:

Smoking (smoking): a two-level factor with levels no and yes.
M. Work (strenuous mental work): a two-level factor with levels no and yes.
P. Work (strenuous physical work): a two-level factor with levels no and yes.
Pressure (systolic blood pressure): a two-level factor with levels <140 and >140.
Proteins (ratio of beta and alpha lipoproteins): a two-level factor with levels <3 and >3.
Family (family anamnesis of coronary heart disease): a two-level factor with levels neg and pos.

Source

Edwards DI (2000). Introduction to Graphical Modelling. Springer, 2nd edition.

Reinis Z, Pokorny J, Basika V, Tiserova J, Gorican K, Horakova D, Stuchlikova E, Havranek T, Hrabovsky F (1981). "Prognostic Significance of the Risk Profile in the Prevention of Coronary Heart Disease". Bratisl Lek Listy, 76:137–150. Published on Bratislava Medical Journal, in Czech.

Whittaker J (1990). Graphical Models in Applied Multivariate Statistics. Wiley.

Examples


# This is the undirected graphical model from Whittaker (1990).
data(coronary)
ug = empty.graph(names(coronary))
arcs(ug, check.cycles = FALSE) = matrix(
  c("Family", "M. Work", "M. Work", "Family",
    "M. Work", "P. Work", "P. Work", "M. Work",
    "M. Work", "Proteins", "Proteins", "M. Work",
    "M. Work", "Smoking", "Smoking", "M. Work",
    "P. Work", "Smoking", "Smoking", "P. Work",
    "P. Work", "Proteins", "Proteins", "P. Work",
    "Smoking", "Proteins", "Proteins", "Smoking",
    "Smoking", "Pressure", "Pressure", "Smoking",
    "Pressure", "Proteins", "Proteins", "Pressure"),
  ncol = 2, byrow = TRUE,
  dimnames = list(c(), c("from", "to")))
## Not run: graphviz.plot(ug, shape = "ellipse")

bnlearn documentation built on Sept. 11, 2024, 8:27 p.m.