findOptimalApproxDesign: Find an Optimal Approximate Design for Poisson Regression

In designGLMM: Finding Optimal Block Designs for a Generalised Linear Mixed Model

Description

This function will calculate the design weights for an A-optimal completely randomised design with a Poisson response.

Usage

findOptimalApproxDesign(means, silent = FALSE)

Arguments

means	A list of length v containing conditional means for each treatment e.g. c(1,1,2) for three treatments with means 1, 1, and 2 respectively
silent	a logical to indicate whether the design should be supressed out (TRUE) or not (FALSE)

Value

design

A list of the same dimension as means that contains the design weights for the corresponding treatments.

Author(s)

Stephen Bush ([e-mail])

Katya Ruggiero ([e-mail])

References

Bush, S., and Ruggiero, K. (2016) Optimal block designs for experiments with responses drawn from a Poisson distribution, Under Review, preprint available at http://arxiv.org/abs/1601.00477

See Also

findOptimalExactDesign, findOptimalBlockDesign

Examples

# Calculating design weights for an approximate design with means 1, 2, and 4

findOptimalApproxDesign(c(1,2,4), silent = FALSE)

designGLMM documentation built on May 2, 2019, 2:51 p.m.