Created
June 14, 2010 19:57
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Example use of R HMM package
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| library("RHmm") | |
| sunProb <- c(0.6, 0.2, 0.15, 0.05) | |
| cloudProb <- c(0.25, 0.25, 0.25, 0.25) | |
| rainProb <- c(0.05, 0.10, 0.35, 0.50) | |
| weatherDist <- distributionSet(dis="DISCRETE", proba=list(sunProb, cloudProb, rainProb), labels =c("DRY", "DRYISH", "DAMP", "SOGGY")) | |
| weatherTransitions <- rbind(c(0.5, 0.375, 0.125), c(0.25, 0.125, 0.625), c(0.25, 0.375, 0.375)) | |
| weatherHmm <- HMMSet(initProb=c(0.63, 0.17, 0.20), transMat=weatherTransitions, distribution=weatherDist) | |
| weatherPath <- viterbi(HMM=weatherHmm, obs=c("DRY", "DAMP", "SOGGY", "SOGGY", "DRYISH")) | |
| weatherPath |
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Hi , How do I do the same thing in case I have two hidden columns. For example my Dataset has 1st column X with possible values (a. b, c) and 2nd Column Y with possible values as (d, e, f) and my 3rd column which is the observed column be Z with possible set of values as (g, h, i). How do I create my distribution set in this case?