ctracelr {smoothemplik} | R Documentation |
Compute empirical likelihood on a trajectory
Description
Compute empirical likelihood on a trajectory
Usage
ctracelr(
z,
ct = NULL,
mu0,
mu1,
N = 5,
verbose = FALSE,
verbose.solver = FALSE,
...
)
Arguments
z |
Passed to |
ct |
Passed to |
mu0 |
Starting point of trajectory |
mu1 |
End point of trajectory |
N |
Number of segments into which the path is split (i. e. |
verbose |
Logical: report iteration data? |
verbose.solver |
Logical: report internal iteration data from the optimiser? Very verbose. |
... |
Passed to This function does not accept the starting lambda because it is much faster (3–5 times) to reuse the lambda from the previous iteration. |
Value
A matrix with one row at each mean from mu0 to mu1 and a column for each EL return value (except EL weights).
Examples
# Plot 2.5 from Owen (2001)
earth <- c(
5.5, 5.61, 4.88, 5.07, 5.26, 5.55, 5.36, 5.29, 5.58, 5.65, 5.57, 5.53, 5.62, 5.29,
5.44, 5.34, 5.79, 5.1, 5.27, 5.39, 5.42, 5.47, 5.63, 5.34, 5.46, 5.3, 5.75, 5.68, 5.85
)
weightedEL(earth, mu = 5.1, verbose = TRUE)
logELR <- ctracelr(earth, mu0 = 5.1, mu1 = 5.65, N = 55, verbose = TRUE)
hist(earth, breaks = seq(4.75, 6, 1/8))
plot(logELR[, 1], exp(logELR[, 2]), bty = "n", type = "l",
xlab = "Earth density", ylab = "ELR")
# TODO: why is there non-convergence in row 0?
# Two-dimensional trajectory
set.seed(1)
xy <- matrix(rexp(200), ncol = 2)
logELR2 <- ctracelr(xy, mu0 = c(0.5, 0.5), mu1 = c(1.5, 1.5), N = 100)
[Package smoothemplik version 0.0.14 Index]