daugment_design: D-Augment Design

In optedr: Calculating Optimal and D-Augmented Designs

D-Augment Design

Description

D-Augments a design. The user gives an initial design for which he would like to add points and specifies the weight of the new points. Then he is prompted to choose a minimum efficiency. After that, the candidate points region is calculated and the user can choose the points and weights to add.

Usage

daugment_design(
  init_design,
  alpha,
  model,
  parameters,
  par_values,
  design_space,
  calc_optimal_design,
  weight_fun = function(x) 1
)

Arguments

init_design	dataframe with "Point" and "Weight" columns that represents the initial design to augment
alpha	combined weight of the new points
model	formula that represents the model with x as the independent variable
parameters	character vector with the unknown parameters of the model to estimate
par_values	numeric vector with the initial values of the unknown parameters
design_space	numeric vector with the limits of the space of the design
calc_optimal_design	boolean parameter, if TRUE, the optimal design is calculated and efficiencies of the initial and augmented design are given
weight_fun	optional one variable function that represents the square of the structure of variance, in case of heteroscedastic variance of the response

Value

A dataframe that represents the D-augmented design

See Also

Other augment designs: dsaugment_design(), laugment_design()

Examples

init_des <- data.frame("Point" = c(30, 60, 90), "Weight" = c(1/3, 1/3, 1/3))
augment_design("D-Optimality", init_des, 0.25, y ~ 10^(a-b/(c+x)), c("a","b","c"),
  c(8.07131,  1730.63, 233.426), c(1, 100), TRUE)
augment_design("D-Optimality", init_des, 0.25, y ~ 10^(a-b/(c+x)), c("a","b","c"),
  c(8.07131,  1730.63, 233.426), c(1, 100), FALSE)

optedr documentation built on Nov. 18, 2022, 5:12 p.m.