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 a
and
b
such that P(a<x<b) = 1-\alpha
.
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]