Description Usage Arguments Value See Also Examples
Run a Markov-chain Monte Carlo algorithm to sample from the log posterior density.
1 2 3 |
data |
A named list with the dataset. |
writeDir |
An optional character string with the path where the Stan file should be written. Useful to inspect and modify the Stan code manually. It defaults to a temporary directory. |
... |
Arguments to be passed to rstan's |
An object of S4 class stanfit with some additional attributes (the dataset data, the name of the Stan code file filename, and the Specification
object spec). This object is completely compatible with all other functions.
See rstan's sampling
for further details on tunning the MCMC algorithm.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ## Not run:
y <- rnorm(1000) # Assume this is your dataset
mySpec <- hmm(
K = 2, R = 1,
observation = Gaussian(
mu = Gaussian(0, 10),
sigma = Student(
mu = 0, sigma = 10, nu = 1, bounds = list(0, NULL)
)
),
initial = Dirichlet(alpha = c(1, 1)),
transition = Dirichlet(alpha = c(1, 1)),
name = "Univariate Gaussian Hidden Markov Model"
)
myModel <- compile(mySpec)
myFit <- draw_samples(myModel, y = y, chains = 2, iter = 500)
## End(Not run)
|
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