ForecastHMMconfint: Forecasted confidence interval of a univariate HMM at times...

In GenHMM1d: Goodness-of-Fit for Univariate Hidden Markov Models

Description

This function computes the forecasted confidence interval of a univariate HMM for multiple horizons, given observations up to time n

Usage

ForecastHMMconfint(U, family, theta, Q, eta, k = 1)

Arguments

U	values between 0 and 1
family	distribution name; run the function distributions() for help
theta	parameters; (r x p)
Q	probability transition matrix; (r x r)
eta	vector of the estimated probability of each regime at time n; (1 x r)
k	prediction times (may be a vector of integers).

Value

qlow	lower bound of the forecasted confidence interval
qhigh	upper bound of the forecasted confidence interval

Examples

family = "gaussian"

theta = matrix(c(-1.5, 1.7, 1, 1),2,2)
Q = matrix(c(0.8, 0.3, 0.2, 0.7), 2, 2)
eta = c(0.96091218, 0.03908782)

forecastedhmmconfint = ForecastHMMconfint(U=c(0.1, 0.9), family, theta=theta, Q=Q,
eta=eta, k=c(1,2,3,4,5))
print('Forecasted confidence interval : ')
print(forecastedhmmconfint)

GenHMM1d documentation built on Jan. 21, 2021, 9:07 a.m.