View source: R/efficient_round.R
combinatorial_round | R Documentation |
Given an approximate design and a number of points, computes all the possible combinations of roundings of each point to the nearest integer, keeps the ones that amount to the requested number of points, and returns the one with the best value for the criterion function
combinatorial_round(
design,
n,
criterion = NULL,
model = NULL,
parameters = NULL,
par_values = NULL,
weight_fun = function(x) 1,
par_int = NULL,
reg_int = NULL,
matB = NULL
)
design |
either a dataframe with the design to round, or an object of class "optdes". If the former, the criterion, model and parameters must be specified. The dataframe should have two columns:
|
n |
integer with the desired number of points of the resulting design. |
criterion |
character variable with the chosen optimality criterion. Can be one of the following:
|
model |
formula describing the model. Must use x as the variable. |
parameters |
character vector with the parameters of the models, as written in the |
par_values |
numeric vector with the parameters nominal values, in the same order as given in |
weight_fun |
optional one variable function that represents the square of the structure of variance, in case of heteroscedastic variance of the response. |
par_int |
optional numeric vector with the index of the |
matB |
optional matrix of dimensions k x k, for L-optimality. |
A data.frame with the rounded design to n number of points
aprox_design <- opt_des("D-Optimality", y ~ a * exp(-b / x), c("a", "b"), c(1, 1500), c(212, 422))
combinatorial_round(aprox_design, 27)
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