Wynn: Wynn
In arappold/docopulae: Optimal Designs for Copula Models

Description Usage Arguments Details Value References See Also Examples

Wynn finds an optimal design using a sensitivity function and a Wynn-algorithm.

1	Wynn(sensF, tol, maxIter = 10000)

`sensF`	`function(x=NULL, desw=NULL, desx=NULL, mod=NULL)`, a sensitivity function. It's attribute `"defaults"` shall contain identical `x` and `desx`, and `sensF(desw=w)` shall return sensitivities corresponding to each point in `x`.
`tol`	the tolerance level regarding the sensitivities.
`maxIter`	the maximum number of iterations.

See Dsensitivity and it's return value for a reference implementation of a function complying with the requirements for sensF.

The algorithm starts from a uniform weight design. In each iteration weight is redistributed to the point which has the highest sensitivity. Sequence: 1/i. The algorithm stops when all sensitivities are below a specified tolerance level or the maximum number of iterations is reached.

Wynn returns an object of class "desigh". See design for its structural definition.

Wynn, Henry P. (1970) The Sequential Generation of D-Optimum Experimental Designs. The Annals of Mathematical Statistics, 41(5):1655-1664.

Dsensitivity, design