R: Evaluates a design.

eval.design {AlgDesign} | R Documentation

## Evaluates a design.

### Description

A design is evaluated.

### Usage

    eval.design(frml,design,confounding=FALSE,variances=TRUE,center=FALSE,X=NULL)

### Arguments

`frml` | The formula used to create the design.
`design` | The design, which may be the design part of the output of optFederov().
`confounding` | If confounding=TRUE, the confounding patterns will be shown.
`variances` | If TRUE, the variances each term will be output.
`center` | If TRUE, numeric variables will be centered before frml is applied.
`X` | X is either the matrix describing the prediction space for I or for G, the the candidate set from which the design was chosen. They are often the same.

### Value

`confounding` | A matrix. The columns of which give the regression coefficients of each variable regressed on the others. If C is the confounding matrix, then -ZC is a matrix of residuals of the variables regressed on the other variables.
`determinant` | (det(M/N)^(1/k), where M=Z'Z/N, and Z is the model expanded N x k design matrix.
`A` | The average coefficient variance: trace(Mi)/k, where Mi is the inverse of M.
`I` | The average prediction variance over X, which can be shown to be trace((X'X*Mi)/N.
`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 – i.e. the max of x'(Mi)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).
`diagonality` | The diagonality of the design, excluding the constant, if any. Diagonality is defined as (|M1|/prod(diag(M1)))^(1/k), where M1 is M with first column and row deleted when there is a constant.
`gmean.variances` | The geometric mean of the coefficient variances.

### Note

I, Ge and Dea are calculated only when X is input.

### Author(s)

Bob Wheeler bwheelerg@gmail.com

Please cite this program as follows:

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

[Package AlgDesign version 1.1-7.3 Index]