Displaying 1 result from an estimated 1 matches for "p_si_t_1_sj".
2011 Dec 01
1
Estimation of AR(1) Model with Markov Switching
...-1)
f_s1 <- rep(0,nrow(X)-1)
f <- rep(0,nrow(X)-1)
logf <- rep(0, nrow(X)-1)
p_s0_t[1] <- p0_s0
p_s1_t[1] <- p0_s1
# initiate hamilton filter
for(i in 2:nrow(X)) {
# calculate prior probabilities using the TPT
# TPT for this example gives us
# p_si_t_1 = p_si_t_1_si * p_si_t + p_si_t_1_sj * p_si_t
# where p_si_t_1 is the prob state_t = i given information @ time t-1
# p_si_t_1_sj is the prob state_t = i given state_t_1 = j, and all info @
time t-1
# p_si_t is the prob state_t = i given information @ time t
# in this simple example p_si_t_1_sj = p_si_sj
p_s0_t_1[i] <- (p_s0_s0 *...