depmixS4 - How to fit HMM usgin multiple sequences of observation Is there any R package that supports fitting an HMM using multiple sequences of observations? to the best of my knowledge depmixS4 does not support this feature
No, depmixS4 supports multiple external variables to be included to forecast underlying time series.   In this case transition matrix is a function of all the other external variables. It is given in depmix S4 vignette also.-

a useful material for start -
https://machinelearningstories.blogspot.com/2017/02/hidden-markov-model-session-1.html &amp;
http://machinelearningstories.blogspot.in/2017_03_01_archive.html

R Code snippets- 

Required library

library(depmixS4)

data loading-

physician_prescrition_data &lt;-c(12,16,45,45,56,67,78,98,120,124,156)

model execution-

HMM_model &lt;- depmixS4::depmix(physician_prescrition_data~1, nstates = 2,ntimes=length(physician_prescrition_data))

model fitting

HMM_fm &lt;- fit(HMM_model)

Transition probabilties-

HMM_fm@transition

posterior states-

posterior(HMM_fm)
plot(ts(posterior(HMM_fm)[,1]))

Emission probabilties-

HMM_fm@response