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p_s0_s1
2011 Dec 01
1
Estimation of AR(1) Model with Markov Switching
...construct negative conditional likelihood function
neg.logl <- function(theta, data) {
# construct parameters
beta_s0 <- theta[1:2]
beta_s1 <- theta[3:4]
sigma2 <- exp(theta[5])
gamma0 <- theta[6]
gamma1 <- theta[7]
# construct probabilities
#probit specification
p_s0_s0 <- pnorm(gamma_s0)
p_s0_s1 <- pnorm(gamma_s1)
p_s1_s0 <- 1-pnorm(gamma_s0)
p_s1_s1 <- 1-pnorm(gamma_s1)
# create data matrix
X <- cbind(1,y)
# assume erogodicity of the markov chain
# use unconditional probabilities
p0_s0 <- (1 - p_s1_s1) / (2 -p_s0_s0 -p_s1_s1)
p0_s1 <- 1...