model: Functions related to finding models

In llrs/inteRmodel: Find Models of Interaction

Functions related to finding models

Description

Look for every variation of the models changing the weights by 0.1.

Usage

iterate_model(..., BPPARAM = BiocParallel::SerialParam())

search_model(..., nWeights = 3, BPPARAM = BiocParallel::SerialParam())

Arguments

...	All the same arguments that would be passed to sggca, pass named arguments.
BPPARAM	Set up parallel backend (see BiocParallel documentation).
nWeights	The number of weights used to check the possible designs.

Value

A matrix with the design of the model

Functions

• search_model: Search for the right model for the blocks provided.

See Also

sgcca

Examples

data("Russett", package = "RGCCA")
X_agric <- as.matrix(Russett[, c("gini", "farm", "rent")])
X_ind <- as.matrix(Russett[, c("gnpr", "labo")])
X_polit <- as.matrix(Russett[ , c("inst", "ecks",  "death", "demostab",
                                  "dictator")])
A <- list(Agric = X_agric, Ind = X_ind, Polit = X_polit)
C <- matrix(c(0, 0, 1, 0, 0, 1, 1, 1, 0), 3, 3)
out <- search_model(A = A, C = C, c1 =rep(1, 3), scheme = "factorial",
               scale = FALSE, verbose = FALSE,
               ncomp = rep(1, length(A)),
               bias = TRUE, BPPARAM = BiocParallel::SerialParam())
head(out)
# From all the models, we select that with the higher inner AVE:
model <- extract_model(C, out, "inner")
# We then look for a variation of the weights of this model
out <- iterate_model(A = A, C = model, c1 =rep(1, 3), scheme = "factorial",
               scale = FALSE, verbose = FALSE,
               ncomp = rep(1, length(A)),
               bias = TRUE)

llrs/inteRmodel documentation built on April 1, 2022, 4:04 p.m.