classical_lsq {structToolbox}R Documentation

Classical Least Squares regression

Description

Classical least squares, where y is the response and X is the design matrix, applied to each feature individually. Here the response is taken from the data matrix and the design matrix is the taken from the specified sample meta data column.

Usage

classical_lsq(alpha = 0.05, mtc = "fdr", factor_names, intercept = TRUE, ...)

Arguments

alpha

p-value threshold for determining significance. Default alpha = 0.05.

mtc

multiple test correction method to apply. Can be: holm, hochberg, hommel, bonferroni, BH, BY, fdr or none

factor_names

the column name(s) of sample_meta to use

intercept

[TRUE] or FALSE to include an intercept term in the fit

...

additional slots and values passed to struct_class

Value

A STRUCT method object with functions for applying classical least squares

struct object

Examples

D = iris_DatasetExperiment()
M = classical_lsq(factor_names = 'Species')
M = model_apply(M,D)


[Package structToolbox version 1.0.1 Index]