Function to check that the inputs given to the function opt_des are correct. If not, throws the
correspondent error message.
check_inputs(
criterion,
model,
parameters,
par_values,
design_space,
init_design,
join_thresh,
delete_thresh,
delta,
tol,
tol2,
par_int,
matB,
reg_int,
desired_output,
weight_fun
)character variable with the chosen optimality criterion. Can be one of the following:
'D-Optimality'
'Ds-Optimality'
'A-Optimality'
'I-Optimality'
'L-Optimality'
formula describing the model to calculate the optimal design. Must use x as the variable.
character vector with the parameters of the models, as written in the formula.
numeric vector with the parameters nominal values, in the same order as given in parameters.
numeric vector with the limits of the space of the design.
optional dataframe with the initial design for the algorithm. A dataframe with two columns:
Point contains the support points of the design.
Weight contains the corresponding weights of the Points.
optional numeric value that states how close, in real units, two points must be in order to be joined together by the join heuristic.
optional numeric value with the minimum weight, over 1 total, that a point needs to have in order to not be deleted from the design.
optional numeric value in (0, 1), parameter of the algorithm.
optional numeric value for the convergence of the weight optimizing algorithm.
optional numeric value for the stop criterion: difference between maximum of sensitivity function and optimality criterion.
optional numeric vector with the index of the parameters of interest for Ds-optimality.
optional matrix of dimensions k x k, for L-optimality.
optional numeric vector of two components with the bounds of the interest region for I-Optimality.
not functional yet: decide which kind of output you want.
optional one variable function that represents the square of the structure of variance, in case of heteroscedastic variance of the response.