Bootstrap Method Confidence Intervals
Usage
# S3 method for class 'ctmedboot'
confint(object, parm = NULL, level = 0.95, type = "pc", ...)
Arguments
- object
Object of class
ctmedboot
.- parm
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
- level
the confidence level required.
- type
Charater string. Confidence interval type, that is,
type = "pc"
for percentile;type = "bc"
for bias corrected.- ...
additional arguments.
Examples
if (FALSE) { # \dontrun{
library(bootStateSpace)
# prepare parameters
## number of individuals
n <- 50
## time points
time <- 100
delta_t <- 0.10
## dynamic structure
p <- 3
mu0 <- rep(x = 0, times = p)
sigma0 <- matrix(
data = c(
1.0,
0.2,
0.2,
0.2,
1.0,
0.2,
0.2,
0.2,
1.0
),
nrow = p
)
sigma0_l <- t(chol(sigma0))
mu <- rep(x = 0, times = p)
phi <- matrix(
data = c(
-0.357,
0.771,
-0.450,
0.0,
-0.511,
0.729,
0,
0,
-0.693
),
nrow = p
)
sigma <- matrix(
data = c(
0.24455556,
0.02201587,
-0.05004762,
0.02201587,
0.07067800,
0.01539456,
-0.05004762,
0.01539456,
0.07553061
),
nrow = p
)
sigma_l <- t(chol(sigma))
## measurement model
k <- 3
nu <- rep(x = 0, times = k)
lambda <- diag(k)
theta <- 0.2 * diag(k)
theta_l <- t(chol(theta))
boot <- PBSSMOUFixed(
R = 1000L,
path = getwd(),
prefix = "ou",
n = n,
time = time,
delta_t = delta_t,
mu0 = mu0,
sigma0_l = sigma0_l,
mu = mu,
phi = phi,
sigma_l = sigma_l,
nu = nu,
lambda = lambda,
theta_l = theta_l,
ncores = parallel::detectCores() - 1,
seed = 42
)
phi_hat <- phi
colnames(phi_hat) <- rownames(phi_hat) <- c("x", "m", "y")
phi <- extract(object = boot, what = "phi")
# Specific time interval ----------------------------------------------------
boot <- BootMed(
phi = phi,
phi_hat = phi_hat,
delta_t = 1,
from = "x",
to = "y",
med = "m"
)
confint(boot)
confint(boot, type = "bc") # bias-corrected
# Range of time intervals ---------------------------------------------------
boot <- BootMed(
phi = phi,
phi_hat = phi_hat,
delta_t = 1:5,
from = "x",
to = "y",
med = "m"
)
confint(boot)
confint(boot, type = "bc") # bias-corrected
} # }