Hi Patrick
I understand this might be trivial but I feel this can help others better understand the time handling in DAPPER. I find the definition of HMM.tseq.Ko a bit confusing.
I can understand that the whole trajectory is K+1 with K being the number of forecast time steps (len(kk) == len(tt) == K + 1), and 1 is the initial condition.
But the logic of having len(kko) == len(tto) == Ko+1 is unclear to me. The only reason that I can think of is to match the definition of K. However, we don't have any observation values at initial step, so in the end, when I try to describe Ko, it is always the number of observations minus one. I feel this is an unconventional concept.
Hi Patrick
I understand this might be trivial but I feel this can help others better understand the time handling in DAPPER. I find the definition of
HMM.tseq.Koa bit confusing.I can understand that the whole trajectory is
K+1withKbeing the number of forecast time steps (len(kk) == len(tt) == K + 1), and1is the initial condition.But the logic of having
len(kko) == len(tto) == Ko+1is unclear to me. The only reason that I can think of is to match the definition ofK. However, we don't have any observation values at initial step, so in the end, when I try to describeKo, it is always the number of observations minus one. I feel this is an unconventional concept.