R语言中的HMM算法相关的包_akka9981

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R语言中的HMM算法相关的包

(2013-05-28 10:29:48)

标签：

r

hmm

杂谈

分类：统计

Example 1:
library(HMM)

# Initialise HMM

hmm = initHMM(c("A","B"), c("L","R"),
transProbs=matrix(c(.8,.2,.2,.8),2),

emissionProbs=matrix(c(.6,.4,.4,.6),2))

print(hmm)

# Sequence of observations

observations = c("L","L","R","R")

# Calculate backward probablities

logBackwardProbabilities =
backward(hmm,observations)

print(exp(logBackwardProbabilities))


Example 2:

library(HMM)

# Initial HMM
hmm = initHMM(c("A","B"),c("L","R"),
transProbs=matrix(c(.9,.1,.1,.9),2),

emissionProbs=matrix(c(.5,.51,.5,.49),2))
print(hmm)
# Sequence of observation
a = sample(c(rep("L",100),rep("R",300)))
b = sample(c(rep("L",300),rep("R",100)))
observation = c(a,b)
# Baum-Welch
bw = baumWelch(hmm,observation,10)
print(bw$hmm)


Example 3:

library(HMM)

# Initialise HMM
hmm = initHMM(c("A","B"), c("L","R"),
transProbs=matrix(c(.8,.2,.2,.8),2),
emissionProbs=matrix(c(.6,.4,.4,.6),2))
print(hmm)
# Sequence of observations
observations = c("L","L","R","R")
# Calculate forward probablities
logForwardProbabilities =
forward(hmm,observations)
print(exp(logForwardProbabilities))


Example 4:

library(HMM)

# Initialise HMM
hmm = initHMM(c("A","B"), c("L","R"),
transProbs=matrix(c(.8,.2,.2,.8),2),
emissionProbs=matrix(c(.6,.4,.4,.6),2))
print(hmm)
# Sequence of observations
observations = c("L","L","R","R")
# Calculate posterior probablities of the
states

posterior = posterior(hmm,observations)
print(posterior)


Example 5:

library(HMM)

# Initialise HMM
hmm = initHMM(c("A","B"), c("L","R"),
transProbs=matrix(c(.6,.4,.4,.6),2),
emissionProbs=matrix(c(.6,.4,.4,.6),2))
print(hmm)
# Sequence of observations
observations = c("L","L","R","R")
# Calculate Viterbi path
viterbi = viterbi(hmm,observations)
print(viterbi)


Example 6:

library(HMM)

# Initial HMM
hmm = initHMM(c("A","B"),c("L","R"),
transProbs=matrix(c(.9,.1,.1,.9),2),

emissionProbs=matrix(c(.5,.51,.5,.49),2))
print(hmm)
# Sequence of observation
a = sample(c(rep("L",100),rep("R",300)))
b = sample(c(rep("L",300),rep("R",100)))
observation = c(a,b)
# Viterbi-training
vt = viterbiTraining(hmm,observation,10)
print(vt$hmm)

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