generateNormalPriorData {MoTBFs} | R Documentation |
Generate a prior dataset taking in to account the relationships between varibles inside a given network.
generateNormalPriorData(graph, data, size, means, deviations = NULL)
graph |
A network of the class |
data |
A datase of class |
size |
A |
means |
A |
deviations |
A |
A normal prior data set of class "data.frame"
.
## Data
data(ecoli)
data <- ecoli[,-c(1,9)] ## remove sequece.name and class
X <- TrainingandTestData(data, percentage_test = 0.95)
Xtraining <- X$Training
Xtest <- X$Test
## DAG
dag <- LearningHC(data)
plot(dag)
## Means and desviations
colnames(data)
m <- sapply(data, mean)
m <- m[-which(is.na(m))]
names(m)
d <- sapply(data, sd)
d <- d[-which(is.na(m))]
names(d)
## Prior Dataset
n <- 5600
priorData <- generateNormalPriorData(dag, data = Xtraining, size = n, means = m)
summary(priorData)
ncol(priorData)
nrow(priorData)
class(priorData)