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asia {bnlearn}  R Documentation 
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 twolevel factor with levelsyes
andno
. 
T
(tuberculosis), a twolevel factor with levelsyes
andno
. 
L
(lung cancer), a twolevel factor with levelsyes
andno
. 
B
(bronchitis), a twolevel factor with levelsyes
andno
. 
A
(visit to Asia), a twolevel factor with levelsyes
andno
. 
S
(smoking), a twolevel factor with levelsyes
andno
. 
X
(chest Xray), a twolevel factor with levelsyes
andno
. 
E
(tuberculosis versus lung cancer/bronchitis), a twolevel factor with levelsyes
andno
.
Note
Lauritzen and Spiegelhalter (1988) motivate this example as follows:
“Shortnessofbreath (dyspnoea) may be due to tuberculosis, lung cancer or bronchitis, or none of them, or more than one of them. A recent visit to Asia increases the chances of tuberculosis, while smoking is known to be a risk factor for both lung cancer and bronchitis. The results of a single chest Xray do not discriminate between lung cancer and tuberculosis, as neither does the presence or absence of dyspnoea.”
Standard learning algorithms are not able to recover the true structure of the network because of the
presence of a node (E
) with conditional probabilities equal to both 0 and 1. Monte Carlo tests
seems to behave better than their parametric counterparts.
The complete BN can be downloaded from http://www.bnlearn.com/bnrepository.
Source
Lauritzen S, Spiegelhalter D (1988). "Local Computation with Probabilities on Graphical Structures and their Application to Expert Systems (with discussion)". Journal of the Royal Statistical Society: Series B, 50(2):157–224.
Examples
# load the data. data(asia) # create and plot the network structure. dag = model2network("[A][S][TA][LS][BS][DB:E][ET:L][XE]") ## Not run: graphviz.plot(dag)
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