infmat: Information matrix of a design

In OptimalDesign: A Toolbox for Computing Efficient Designs of Experiments

Information matrix of a design

Description

Computes the information matrix of a design w in the model determined by the matrix Fx of candidate regressors.

Usage

infmat(Fx, w, echo=TRUE)

Arguments

Fx	the n times m matrix of candidate regressors (as rows), where n is the number of candidate design points and m (where m>=2, m<=n) is the number of parameters.
w	a non-negative vector of length n representing the design.
echo	Print the call of the function?

Value

The information matrix of the design w in the model with all candidate regresors given by the rows of Fx.

Note

The information matrix is standardized, i.e., it assumes that the variance of the errors is 1.

Author(s)

Radoslav Harman, Lenka Filova

See Also

optcrit

Examples

# Compute its information matrix for the design that is
# uniform on all the points with at most two levels equal to 1
# in the main effects model with 2 factors.

Fx <- Fx_cube(~x1 + x2 + x3 + x4 + x5, lower = rep(0, 5))
w <- rep(0, 2^5)
for (i in 1:(2^5)) if (sum(Fx[i, 2:6]) <= 2) w[i] <- 1
print(M <- infmat(Fx, w))

## Not run: 
# Visualize the correlation matrix of the parameter estimators

V <- solve(M); Y <- diag(1/sqrt(diag(V)))
library(corrplot); corrplot(Y %*% V %*% Y)

## End(Not run)

OptimalDesign documentation built on June 8, 2025, 12:08 p.m.