get_augment_region {optedr}

Get Augment Regions

Description

Given a model and criterion, calculates the candidate points region. 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.

Usage

get_augment_region(
  criterion,
  init_design,
  alpha,
  model,
  parameters,
  par_values,
  design_space,
  calc_optimal_design,
  par_int = NA,
  matB = NA,
  distribution = NA,
  weight_fun = function(x) 1
)

Arguments

criterion

character with the chosen optimality criterion. Can be one of the following:

• 'D-Optimality'

• 'Ds-Optimality'

• 'A-Optimality'

• 'I-Optimality'

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 represent 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

par_int

optional numeric vector with the index of the parameters of interest for Ds-optimality.

matB

optional matrix of dimensions k x k, integral of the information matrix of the model over the interest region for I-optimality.

distribution

character specifying the probability distribution of the response. Can be one of the following:

• 'Homoscedasticity'

• 'Gamma', which can be used for exponential or normal heteroscedastic with constant relative error

• 'Poisson'

• 'Logistic'

• 'Log-Normal' (work in progress)

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 vector of the points limiting the candidate points region

Examples

init_des <- data.frame("Point" = c(30, 60, 90), "Weight" = c(1/3, 1/3, 1/3))
get_augment_region("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)
get_augment_region("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)