squantCI

0th

Percentile

Simulation-quantile based confidence intervals.

Calculates estimates of confidence intervals for the parameters of a model fitted by hmm.discnp. Uses a method based quantiles of estimates produced by simulation (or “parametric bootstrapping”).

Keywords
utility
Usage
squantCI(object, seed = NULL, alpha = 0.05, nsim=100, verbose = TRUE)
Arguments
object

An object of class hmm.discnp as returned by hmm().

seed

Integer scalar serving as a seed for the random number generator. If left NULL the seed itself is chosen randomly from the set of integers between 1 and \(10^5\).

alpha

Positive real number strictly between 0 and 1. A set of 100*(1-alpha)% confidence intervals will be produced.

nsim

A positive integer. The number of simulations upon which the confidence interval estimates will be based.

verbose

Logical scalar; if TRUE, iteration counts will be printed out during each of the simulation and model-fitting stages.

Details

This function is currently applicable only to models fitted to univariate data. The confidence intervals calculated are for the “raw” parameters (entries of tpm with the last column dropped --- since the rows sum to 1, and the entries of Rho with the last row dropped --- since the columns sum to 1.

Value

A 2-by-npar matrix (where npar is the number of “independent” parameters in the model) whose columns form the estimated confidence intervals. The column labels indicate the parameters to which each column pertains, in a reasonably perspicuous manner. The row labels indicate the relevant quantiles in percentages.

This matrix has an attribute seed (the random number generation seed that was used) so that the calculations can be reproduced.

See Also

scovmat() link{rhmm}() link{hmm)}()

Aliases
  • squantCI
Examples
# NOT RUN {
y   <- list(lindLandFlows$deciles,ftLiardFlows$deciles)
fit <- hmm(y,K=3)
CIs <- squantCI(fit,nsim=100)
# }
Documentation reproduced from package hmm.discnp, version 2.1-5, License: GPL (>= 2)

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