simulateHMM: Simulate a hidden Markov model path (HMM)
In plbaldoni/mixHMM: Differential Peak Calling via Hidden Markov Model With Mixture of Negative Binomial Distributions
Description
Usage
Arguments
Value
Author(s)
References
Examples
Description
This function simulates a HMM path of size 'm' given a matrix of transition probabilities 'P'. By default, the path always begins at the first state of the HMM.
Usage
1
simulateHMM(P, m)
Arguments
P
a square matrix of transition probabiltiies such that all(rowSums(P)==1) is TRUE
m
length of the HMM path
Value
A vector of integers of length 'm' representing states of the HMM
Author(s)
Pedro L. Baldoni, pedrobaldoni@gmail.com
References
https://github.com/plbaldoni/mixHMM
Examples
1
rle(simulateHMM(P = matrix(c(0.95,0.05,0.05,0.95),2,2),m = 1e4))
plbaldoni/mixHMM documentation built on Nov. 8, 2019, 8:05 p.m.
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Description Usage Arguments Value Author(s) References Examples
Description
This function simulates a HMM path of size 'm' given a matrix of transition probabilities 'P'. By default, the path always begins at the first state of the HMM.
Usage
1 | simulateHMM(P, m)
|
Arguments
P |
a square matrix of transition probabiltiies such that all(rowSums(P)==1) is TRUE |
m |
length of the HMM path |
Value
A vector of integers of length 'm' representing states of the HMM
Author(s)
Pedro L. Baldoni, pedrobaldoni@gmail.com
References
https://github.com/plbaldoni/mixHMM
Examples
1 | rle(simulateHMM(P = matrix(c(0.95,0.05,0.05,0.95),2,2),m = 1e4))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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