Sampling data using Gibbs sampling for use in the examples

Description

Sampling from pairwise binary Markov model using Gibbs sampling. This function is not efficient and only intended to be used in the examples.

Usage

1
BMNSamples(Theta, numSamples, burnIn, skip)

Arguments

Theta

Parameter matrix for the model from which the data is being generated.

numSamples

Number of samples to return.

burnIn

Number of samples to discard as burn in.

skip

Number of samples to discard in-between returned samples.

Details

BMNSamples generates numSamples by using Gibbs sampling. When using Gibbs sampling, it is necessary to discard the initial samples, which is controlled by the parameter burnIn. In order for the drawn samples to be independent, samples in-between also have to be discarded, which is controlled by skip.

Value

Returns a matrix of 0 and 1 of size numSamples times p where p is the number of rows of Theta.

Author(s)

Holger Hoefling

See Also

BMNPseudo, BMNExact