bnlearn (version 1.1)

asia: Asia (synthetic) data set by Lauritzen and Spiegelhalter

Description

Small synthetic data set from Lauritzen and Spiegelhalter (1988) about lung diseases (tuberculosis, lung cancer or bronchitis) and visits to Asia.

Usage

data(asia)

format

The asia data set contains the following variables:

• D(dyspnoea), a two-level factor with levelsyesandno.
• T(tuberculosis), a two-level factor with levelsyesandno.
• L(lung cancer), a two-level factor with levelsyesandno.
• B(bronchitis), a two-level factor with levelsyesandno.
• A(visit to Asia), a two-level factor with levelsyesandno.
• S(smoking), a two-level factor with levelsyesandno.
• X(chest X-ray), a two-level factor with levelsyesandno.
• E(tuberculosis versus lung cancer/bronchitis), a two-level factor with levelsyesandno.

source

S. Lauritzen and D. Spiegelhalter (1988). Local computation with probabilities on graphical structures and their application to expert system. Journal of the Royal Statistics Society - B Series, 50(2), pages 157--192.

Examples

## The modelstring() of this data set is:
# [A][S][T|A][L|S][B|S][D|B][E|T:L][X|E]

# these are the R commands used to generate this data set.
a = sample(c("yes", "no"), 5000, prob = c(0.01, 0.99), replace = TRUE)
s = sample(c("yes", "no"), 5000, prob = c(0.50, 0.50), replace = TRUE)

t = a
t[t == "yes"] = sample(c("yes", "no"), length(which(t == "yes")),
                prob = c(0.05, 0.95), replace = TRUE)
t[t == "no"] = sample(c("yes", "no"), length(which(t == "no")),
                prob = c(0.01, 0.99), replace = TRUE)

l = s
l[l == "yes"] = sample(c("yes", "no"), length(which(l == "yes")),
                prob = c(0.10, 0.90), replace = TRUE)
l[l == "no"] = sample(c("yes", "no"), length(which(l == "no")),
                prob = c(0.01, 0.99), replace = TRUE)

b = s
b[b == "yes"] = sample(c("yes", "no"), length(which(b == "yes")),
                prob = c(0.60, 0.40), replace = TRUE)
b[b == "no"] = sample(c("yes", "no"), length(which(b == "no")),
                prob = c(0.30, 0.70), replace = TRUE)

e = apply(cbind(l,t), 1, paste, collapse= ":")
e[e == "yes:yes"] = "yes"
e[e == "yes:no"] = "yes"
e[e == "no:yes"] = "yes"
e[e == "no:no"] = "no"

x = e
x[x == "yes"] = sample(c("yes", "no"), length(which(x == "yes")),
                prob = c(0.98, 0.02), replace = TRUE)
x[x == "no"] = sample(c("yes", "no"), length(which(x == "no")),
                prob = c(0.05, 0.95), replace = TRUE)

d = apply(cbind(e,b), 1, paste, collapse= ":")
d[d == "yes:yes"] = sample(c("yes", "no"), length(which(d == "yes:yes")),
                    prob = c(0.90, 0.10), replace = TRUE)
d[d == "yes:no"] = sample(c("yes", "no"), length(which(d == "yes:no")),
                    prob = c(0.70, 0.30), replace = TRUE)
d[d == "no:yes"] = sample(c("yes", "no"), length(which(d == "no:yes")),
                   prob = c(0.80, 0.20), replace = TRUE)
d[d == "no:no"] = sample(c("yes", "no"), length(which(d == "no:no")),
                  prob = c(0.10, 0.90), replace = TRUE)

data.frame(A = a, S = s, T = t, L = l, B = b, E = e, X = x, D = d)