rodd-package {rodd} | R Documentation |
Optimal Discriminating Designs
Description
This package provides several functions suitable for efficient numerical construction of optimal discriminative designs.
Details
At the current state this package provides the routine tpopt
for the construction of -optimal designs, the routine
KLopt.lnorm
for the calculation of -optimal designs (for lognormal errors) and several auxiliary procedures to represent the results. Function
tpopt
is based on the algorithms that were developed in [7]. Function KLopt.lnorm
is based on the methodology proposed in [8]. See the references for more details.
It is planned to add several new routines for different types of discriminative designs.
References
[1] Atkinson A.C., Fedorov V.V. (1975) The design of experiments for discriminating between two rival models. Biometrika, vol. 62(1), pp. 57–70.
[2] Atkinson A.C., Fedorov V.V. (1975) Optimal design: Experiments for discriminating between several models. Biometrika, vol. 62(2), pp. 289–303.
[3] Dette H., Pepelyshev A. (2008) Efficient experimental designs for sigmoidal growth models. Journal of statistical planning and inference, vol. 138, pp. 2–17.
[4] Dette H., Melas V.B., Shpilev P. (2013) Robust T-optimal discriminating designs. Annals of Statistics, vol. 41(4), pp. 1693–1715.
[5] Braess D., Dette H. (2013) Optimal discriminating designs for several competing regression models. Annals of Statistics, vol. 41(2), pp. 897–922.
[6] Braess D., Dette H. (2013) Supplement to “Optimal discriminating designs for several competing regression models”. Annals of Statistics, online supplementary material.
[7] Dette H., Melas V.B., Guchenko R. (2014) Bayesian T-optimal discriminating designs. ArXiv link.
[8] Dette H., Guchenko R., Melas V.B. (2015) Efficient computation of Bayesian optimal discriminating designs. ArXiv link.