simconf.mc {excursions} | R Documentation |
Simultaneous confidence regions using Monte Carlo samples
Description
simconf.mc
is used for calculating simultaneous confidence regions based
on Monte Carlo samples. The function returns upper and lower bounds and
such that
.
Usage
simconf.mc(samples, alpha, ind, verbose = FALSE)
Arguments
samples |
Matrix with model Monte Carlo samples. Each column contains a sample of the model. |
alpha |
Error probability for the region. |
ind |
Indices of the nodes that should be analyzed (optional). |
verbose |
Set to TRUE for verbose mode (optional). |
Details
See simconf
for details.
Value
An object of class "excurobj" with elements
a |
The lower bound. |
b |
The upper bound. |
a.marginal |
The lower bound for pointwise confidence bands. |
b.marginal |
The upper bound for pointwise confidence bands. |
Author(s)
David Bolin davidbolin@gmail.com
See Also
Examples
## Create mean and a tridiagonal precision matrix
n <- 11
mu.x <- seq(-5, 5, length = n)
Q.x <- Matrix(toeplitz(c(1, -0.1, rep(0, n - 2))))
## Sample the model 100 times (increase for better estimate)
X <- mu.x + solve(chol(Q.x), matrix(rnorm(n = n * 100), nrow = n, ncol = 100))
## calculate the confidence region
conf <- simconf.mc(X, 0.2)
## Plot the region
plot(mu.x,
type = "l", ylim = c(-10, 10),
main = "Mean (black) and confidence region (red)"
)
lines(conf$a, col = 2)
lines(conf$b, col = 2)
[Package excursions version 2.5.8 Index]