coronary {bnlearn} | 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")

[Package bnlearn version 4.7.1 Index]