cumdist.hmm0norm: Cumulative distribution of an HMM with Extra Zeros
In HMMextra0s: Hidden Markov Models with Extra Zeros

Description Usage Arguments Value Author(s) References Examples

Calculates the cumulative distribution of an HMM with extra zeros.

1	cumdist.hmm0norm(x,HMMest)

`x`	x is a value at which the cumulative distribution is evaluated.
`HMMest`	is a list which contains pie, gamma, sig, mu, and delta (the HMM parameter estimates).

prob

is the calculated cumulative distribution.

Ting Wang

Wang, T., Zhuang, J., Obara, K. and Tsuruoka, H. (2016) Hidden Markov Modeling of Sparse Time Series from Non-volcanic Tremor Observations. Journal of the Royal Statistical Society, Series C, Applied Statistics, 66, Part 4, 691-715.

pie <- c(0.002,0.2,0.4)
gamma <- matrix(c(0.99,0.007,0.003,
                  0.02,0.97,0.01,
                  0.04,0.01,0.95),byrow=TRUE, nrow=3)
mu <- matrix(c(0.3,0.7,0.2),nrow=1)
sig <- matrix(c(0.2,0.1,0.1),nrow=1)
delta <- c(1,0,0)
y <- sim.hmm0norm(mu,sig,pie,gamma,delta, nsim=5000)
R <- as.matrix(y$x,ncol=1)
Z <- y$z
HMMEST <- hmm0norm(R, Z, pie, gamma, mu, sig, delta)
xx <- seq(0,1,0.05)
cumdist <- apply(t(xx),2,cumdist.hmm0norm,HMMest=HMMEST)