calc_phiD {SLSEdesign}

Calculate the loss function of the D-optimal design

Description

Calculate the loss function of the D-optimal design

Usage

calc_phiD(design, theta, FUN, tt, A)

Arguments

design

The resulted design that contains the design points and the associated weights

theta

The parameter value of the model

FUN

The function to calculate the derivative of the given model.

tt

The level of skewness

A

The calculated covariance matrix

Details

This function calculates the loss function of the design problem under the D-optimality. The loss function under D-optimality is defined as the log determinant of the inverse of the Fisher information matrix

Value

The loss of the model at each design points

Examples

my_design <- data.frame(location = c(0, 180), weight = c(1/2, 1/2))
theta <- c(0.05, 0.5)
peleg <- function(xi, theta){
   deno <- (theta[1] + xi * theta[2])^2
   rbind(-xi/deno, -xi^2/deno)
}
A <- matrix(c(1, 0, 0, 0, 0.2116, 1.3116, 0, 1.3116, 15.462521), byrow = TRUE, ncol = 3)
res <- calc_phiA(my_design, theta, peleg, 0, A)
res