plotQNH: Plot transition probabilities
In RJaCGH: Reversible Jump MCMC for the Analysis of CGH Arrays

Description Usage Arguments Details Value Author(s) References Examples

Plot the probabilities of staying in the same state for a non-homogenous hidden Markov model.

1	plotQNH(x, beta, q=-beta, col = NULL, ...)

`x`	Vector of distances between observations
`beta`	beta parameter of the transition matrix. Must be a square matrix with the same size as the number of hidden states
`q`	q parameter of the transition matrix. Must be a square matrix with the same size as the number of hidden states
`col`	vector of colors for each state. Must be of the same size as the number of hidden states
`...`	aditional arguments passed to plot

Please note that RJaCGH model imposes that q is -beta, and distances are normalized to lay between 0 and 1.

A plot is produced showing the probability of staying in the same hidden state versus distance between adjacent genes, for every state.

Oscar M. Rueda and Ramon Diaz-Uriarte

Rueda OM, Diaz-Uriarte R. Flexible and Accurate Detection of Genomic Copy-Number Changes from aCGH. PLoS Comput Biol. 2007;3(6):e122

## Model with two hidden states
## Note that RJaCGH normalizes distances to be between 0 and 1
x <- rexp(99)
x <- x/ max(x)
beta <- matrix(c(0, 1, 3, 0), 2, 2)
plotQNH(x=x, beta=beta, q=-beta, col=c(1,2))