Simulate observations form a hidden Markov model with nonhomogeneous transition probabilities.
Description
This function simulates observations from a hidden Markov model with normal distributed observations and nonhomogeneous transition matrix.
Usage
1  simulateRJaCGH(n, x = NULL, mu, sigma.2, beta, start)

Arguments
n 
Number of observations to simulate 
x 
Distance to the next observation. Must be a vector of size n1 and normalized between zero and one. If NULL, a vector of zeros is taken 
mu 
Vector of means for the hidden states 
sigma.2 
Vector of variances for the hidden states 
beta 

start 
Starting states of the sequence. Must be an integer from 1 to the number of hidden states. 
Details
Please note that in RJaCGH model, parameter q
is taken as beta
Value
A list with components
states 
Sequence of hidden states 
y 
Observations 
Author(s)
Oscar M. Rueda and Ramon DiazUriarte
References
Rueda OM, DiazUriarte R. Flexible and Accurate Detection of Genomic CopyNumber Changes from aCGH. PLoS Comput Biol. 2007;3(6):e122
See Also
Q.NH, RJaCGH
Examples
1 2 3 4 