findOptimalApproxDesign: Find an Optimal Approximate Design for Poisson Regression

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/findOptimalApproxDesign.R

Description

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

Usage

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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 ([email protected])

Katya Ruggiero ([email protected])

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

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# 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 30, 2017, 6:24 a.m.