Fx_dose: Matrix of candidate regressors for a dose-response model
In OptimalDesign: A Toolbox for Computing Efficient Designs of Experiments

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

Creates the matrix of all candidate regressors for a linearization of a dose response model.

1	Fx_dose(dose.levels, theta0, dose.model="emax", echo=TRUE)

`dose.levels`	the `n`-dimensional vector of admissible doses.
`theta0`	the 3-dimensional vector of values of the unknown parameter in which to linearize the model.
`dose.model`	the type of the dose-response model, possible values are `"emax"`, `"loglin"`, and `"exp"`.
`echo`	Print the call of the function?

For mathematical details, see the referenced paper.

The n times 3 matrix of all candidate regressors of a dose-response model linearized in theta0.

Radoslav Harman, Lenka Filova

Dette H, Kiss C, Bevanda M, Bretz F (2010). Optimal designs for the EMAX, log-linear and exponential models. Biometrika, 97(2), 513-518.

Fx_cube, Fx_simplex, Fx_blocks, Fx_glm, Fx_survival

# The loglinear model for the doses 1:150
# Localized at the values of theta0=c(0, 0.0797, 1)
Fx <- Fx_dose(1:150, c(0, 0.0797, 1), dose.model="loglin")

# The locally D-optimal approximate design
w_a <- od_REX(Fx)$w.best
od_plot(Fx, w_a, 1:150)

# The locally D-optimal exact design of size 10
w_e <- od_KL(Fx, 10, t.max=3)$w.best
od_plot(Fx, w_e, 1:150)