linear_model {structToolbox} | R Documentation

## Linear model

### Description

Linear models can be used to carry out regression, single stratum analysis of variance and analysis of covariance.

### Usage

    linear_model(formula, na_action = "na.omit", contrasts = list(), ...)

### Arguments

`formula` | (formula) A symbolic description of the model to be fitted.
`na_action` | (character) NA action. Allowed values are limited to the following: `"na.omit"`: Incomplete cases are removed. `"na.fail"`: An error is thrown if NA are present. `"na.exclude"`: Incomplete cases are removed, and the output result is padded to the correct size using NA. `"na.pass"`: Does not apply a linear model if NA are present. The default is `"na.omit"`.
`contrasts` | (list) The contrasts associated with a factor. The default is `list`.
`...` | Additional slots and values passed to `struct_class`.

### Details

This object makes use of functionality from the following packages:

- `stats`

### Value

A `linear_model` object with the following `output` slots:

`lm` | (lm) The lm object for this model_.
`coefficients` | (numeric) The coefficients for the fitted model_.
`residuals` | (numeric) The residuals for the fitted model_.
`fitted_values` | (numeric) The fitted values for the data used to train the model_.
`predicted_values` | (numeric) The predicted values for new data using the fitted model_.
`r_squared` | (numeric) The value of R Squared for the fitted model_.
`adj_r_squared` | (numeric) The value ofAdjusted R Squared for the fitted model_.

### References

R Core Team (2021). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

### Examples

    D = iris_DatasetExperiment()
    M = linear_model(formula = y~Species)

[Package structToolbox version 1.6.1 Index]