In the Wiki page on the Viterbi Algorithm (https://en.wikipedia.org/wiki/Viterbi_algorithm) there is an example of an HMM describing patients being in states "fever" or "healthy".
What I wish to understand is how I can calculate the transition probabilities, if I have the following info:
Let's assume that the doctor has previously calculated the statistics for the time a patient is healthy, and has a fever.
He concluded that the annual number of days for being "healthy" and with "fever" are distributed normally, with $(\mu_h=350,\sigma_h=5)$ and $(\mu_f=15,\sigma_f=2)$ respectively.
Intuitively the transition probability from "healthy" to "healthy" is much higher than the transition probability from "fever" to "fever".
But how would I calculate the exact probabilities? (Assuming observations are done on a daily basis)