View source: R/distributions.R
rcat.factor | R Documentation |
Matrix version of the categorical distribution. The argument probs
can be a matrix of n rows,
specifying individual (varying in sample) categorical probabilities.
The number of categories generated is equal to ncol(probs)+1
, the levels labeled as: 1,...,ncol(probs)+1
.
rcat.factor(n, probs)
rcategor(n, probs)
n |
Sample size. |
probs |
Either a vector or a matrix of success probabilities.
When |
A factor of length n
with levels: 1,2, ...,ncol(probs)+1
.
rcategor()
: (Deperecated) Random Sample of a Categorical Factor
rcat.b1
, rcat.b0
#---------------------------------------------------------------------------------------
# Specifying and simulating from a DAG with one categorical node with constant
# probabilities
#---------------------------------------------------------------------------------------
D <- DAG.empty()
D <- D + node("race",t=0,distr="rcat.factor",probs=c(0.2,0.1,0.4,0.15,0.05,0.1))
Dset <- set.DAG(D)
simdat <- sim(Dset, n=200, rndseed=1)
#---------------------------------------------------------------------------------------
# Specifying and simulating from a DAG with a categorical node with varying
# probabilities (probabilities are determined by values sampled for nodes L0 and L1)
#---------------------------------------------------------------------------------------
D <- DAG.empty()
D <- D + node("L0", distr="rnorm", mean=10, sd=5)
D <- D + node("L1", distr="rnorm", mean=10, sd=5)
D <- D + node("L2", distr="rcat.factor", probs=c(abs(1/L0), abs(1/L1)))
Dset <- set.DAG(D)
simdat <- sim(Dset, n=200, rndseed=1)
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