Hi,
I am having difficulties estimating the parameters of a HMM using the HMM
package. I have simulated a sequence of observations from a known HMM. When
I estimate the parameters of a HMM using these simulated observations the
parameters are not at all close to the known ones. I realise the estimated
parameters are not going to be exactly the same as the known/true
parameters, but these are nowhere close. Below is my code used. Any ideas
or possible suggestions regarding this issue would be greatly appreciated?
library(HMM)
## DECLARE PARAMETERS OF THE KNOWN MODEL
states = c(1,2,3)
symbols = c(1,2)
startProb = c(0.5,0.25,0.25)
transProb = matrix(c(0.8,0.05,0.15,0.2,0.6,0.2,0.2,0.3,0.5),3,3,TRUE)
emissionProb = matrix(c(0.9,0.1,0.2,0.8,0.7,0.3), 3,2,TRUE)
# CREATE THE KNOWN MODEL
hmmTrue = initHMM(states, symbols, startProb, transProb , emissionProb)
# SIMULATE 1000 OBSERVATIONS OF THE KNOWN MODEL
observation = simHMM(hmmTrue, 1000)
obs = observation$observation
#ESTIMATE A MODEL USING THE OBSERVATIONS GENERATED FROM THE KNOWN MODEL
hmmInit = initHMM(states, symbols, c(1/3,1/3,1/3))
hmmFit = baumWelch(hmmInit, obs)
#The parameters of hmmTrue and hmmFit are not at all alike, why is this?
Kind Regards,
Richard
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