kergp (version 0.5.7)

corLevCompSymm: Correlation Matrix for the Compound Symmetry Structure

Description

Compute the correlation matrix for a the compound symmetry structure.

Usage

corLevCompSymm(par, nlevels, levels, lowerSQRT = FALSE, compGrad = TRUE,
  cov = FALSE, impl = c("C", "R"))

Value

A correlation matrix (or its Cholesky root) with the optional gradient attribute.

Arguments

par

Numeric vector of length 1 if cov is TRUE or with length 2 else. The first element is the correlation coefficient and the second one (when it exists) is the variance.

nlevels

Number of levels.

levels

Character representing the levels.

lowerSQRT

Logical. When TRUE the (lower) Cholesky root \(\mathbf{L}\) of the correlation matrix \(\mathbf{C}\) is returned instead of the correlation matrix.

compGrad

Logical. Should the gradient be computed?

cov

Logical.

If TRUE the matrix is a covariance matrix (or its Cholesky root) rather than a correlation matrix and the last element in par is the variance.

impl

A character telling which of the C and R implementations should be chosen.

Author

Yves Deville

Examples

checkGrad <- TRUE
lowerSQRT <- FALSE
nlevels <- 12
set.seed(1234)
par <- runif(1L, min = 0, max = pi)

##============================================================================
## Compare R and C implementations for 'lowerSQRT = TRUE'
##============================================================================
tR <- system.time(TR <- corLevCompSymm(nlevels = nlevels, par = par,
                                       lowerSQRT = lowerSQRT, impl = "R"))
tC <- system.time(T <- corLevCompSymm(nlevels = nlevels, par = par,
                                      lowerSQRT = lowerSQRT))
tC2 <- system.time(T2 <- corLevCompSymm(nlevels = nlevels, par = par,
                                        lowerSQRT = lowerSQRT, compGrad = FALSE))
## time
rbind(R = tR, C = tC, C2 = tC2)

## results
max(abs(T - TR))
max(abs(T2 - TR))

##===========================================================================
## Compare the gradients
##===========================================================================

if (checkGrad) {

    library(numDeriv)

    ##=======================
    ## lower SQRT case only
    ##========================
    JR <- jacobian(fun = corLevCompSymm, x = par, nlevels = nlevels,
                   lowerSQRT = lowerSQRT, impl = "R", method = "complex")
    J <- attr(T, "gradient")

    ## redim and compare.
    dim(JR) <- dim(J)
    max(abs(J - JR))
    nG <- length(JR)
    plot(1:nG, as.vector(JR), type = "p", pch = 21, col = "SpringGreen3",
         cex = 0.8, ylim = range(J, JR),
         main = paste("gradient check, lowerSQRT =", lowerSQRT))
    points(x = 1:nG, y = as.vector(J), pch = 16, cex = 0.6, col = "orangered")
}