generalizedMatrix {modgo} | R Documentation |
Generalized Lambda and Poisson preparation
Description
Prepare the four moments matrix for GLD and GPD
Usage
generalizedMatrix(
data,
variables = colnames(data),
bin_variables = NULL,
generalized_mode_model = NULL,
multi_sugg_prop = NULL
)
Arguments
data |
a data frame with original variables. |
variables |
a vector of which variables you want to transform. Default:colnames(data) |
bin_variables |
a character vector listing the binary variables. |
generalized_mode_model |
A matrix that contains two columns named "Variables" and "Model". This matrix can be used only if a generalized_mode_model argument is provided. It specifies what model should be used for each Variable. Model values should be "RMFMKL", "RPRS", "STAR" or a combination of them, e.g. "RMFMKL-RPRS" or "STAR-STAR", in case the use wants a bimodal simulation. The user can select Generalized Poisson model for poisson variables, but this model cannot be included in bimodal simulation |
multi_sugg_prop |
A named vector that provides a proportion of value=1 for specific binary variables(=name of the vector) that will be the close to the proportion of this value in the simulated data sets |
Value
A numeric matrix with the four moments for each distribution and a number that corresponds to a GLD model
Author(s)
Francisco M. Ojeda, George Koliopanos
Examples
data("Cleveland",package="modgo")
Variables <- c("Age","STDepression")
Model <- c("rprs", "star-rmfmkl")
model_matrix <- cbind(Variables,
Model)
test_modgo <- generalizedMatrix(data = Cleveland,
generalized_mode_model = model_matrix,
bin_variables = c("CAD","HighFastBloodSugar","Sex","ExInducedAngina"))