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The R package HMMt provides a modified Baum-Welch algorithm that supports multi-dimensional Student's t emission. It also handles NA and provides a 'bridge()' function to uniformize sampling rate. Please do not copy-paste the code. Instead, use 'git clone email@example.com:gui11aume/HMMt.git' to have the full version history. The code is here for reproducibility and mistake-tracking purposes, but feel free to copy, reuse and modify it in any way you like. After installing the package, you can run the following lines of code in R to get started. library(HMMt) x <- c(rt(1000, df=3), rt(1000, df=3)+1) # x has a t distribution with a jump at position 1001. plot(x, type = 'l') # Check the output of BaumWelchT. BaumWelchT(x) # See that it usually finds the transition. lines(BaumWelchT(x)$ViterbiPath-1, col=2)