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 0.99.8 Index]