optFederovC {choiceDes}

Optimal design

Description

INTERNAL: Simplified wrapper for calculating exact algorithmic designs using Federov's exchange algorithm. Based on optFederov in the AlgDesign package.

Usage

optFederovC(modelData, nTrials, nRepeats=5)

Arguments

modelData

The candidate list. A matrix or data frame describing the variables. If a matrix is input and the columns are not named, they will be assigned names X1, X2, etc. Permitted data types include factors or levels- or effects-coded designs.

nTrials

The number of trials in the final design.

nRepeats

The number of times the whole process is repeated.

Details

Generates exact algorithmic designs using Federov's exchange algorithm, and optimizing the D criterion. See optFederov for algorithmic details. A vignette is also available by typing vignette("AlgDesign").

Input data, i.e., modelData, must be of a form that model.matrix(~., modelData results in an effects-coded design or candidate set.

Value

D

The kth root of the generalized variance: det(M)^(1/k), where det(M) is the determinant of the normalized dispersion matrix, or m=Z'Z/n, where Z=X[rows,].

A

The average coefficient variance: trace(M')/k, where M' is the inverse of M.

Ge

The minimax normalized variance over X, expressed as an efficiency with respect to the optimal approximate theory design. It is defined as k/max(d), where max(d) is the maximum normalized variance over X, or the maximum of x'(M')x, over all rows x' of X.

Dea

A lower bound on D efficiency for approximate theory designs. It is equal to exp(1-1/Ge).

design

The design.

rows

A numerical vector of the design row numbers from modelData.

References

Wheeler, R.E. (2004). optFederov. AlgDesign. The R project for statistical computing. (http://www.r-project.org).

Examples

##INTERNAL USE ONLY