S4 class for a summary of LM objects.

## Slots

`coefficients`

A numeric matrix of the results of significance tests.

`intercept`

A single logical for whether the given model has an intercept term or not.

`na.action`

Information returned by

`model.frame`

on the special handling of`NA`

s.`call`

A matched call.

`terms`

A

`terms`

object used.`aliased`

A named logical vector showing if the original coefficients are aliased.

`optim`

A list of the following optimization results:

`par`

A numeric vector of the solution to the (constrained) optimization problem.`lambda`

A numeric vector of the Lagrange multipliers of the dual problem corresponding to`par`

.`iterations`

A single integer for the number of iterations performed.`convergence`

A single logical for the convergence status.`cstr`

A single logical for whether constrained EL optimization is performed or not.

`logl`

A single numeric of the empirical log-likelihood.

`loglr`

A single numeric of the empirical log-likelihood ratio.

`statistic`

A single numeric of minus twice the (constrained) empirical log-likelihood ratio for the overall test.

`df`

A single integer for the degrees of freedom of the statistic.

`pval`

A single numeric for the \(p\)-value of the statistic.

`nobs`

A single integer for the number of observations.

`npar`

A single integer for the number of parameters.

`weighted`

A single logical for whether the data are weighted or not.

`method`

A single character for the method dispatch in internal functions.

`control`

An object of class ControlEL constructed by

`el_control()`

.

## Examples

```
showClass("SummaryLM")
#> Class "SummaryLM" [package "melt"]
#>
#> Slots:
#>
#> Name: coefficients intercept na.action call terms
#> Class: matrix logical ANY call terms
#>
#> Name: aliased optim logl loglr statistic
#> Class: logical list numeric numeric numeric
#>
#> Name: df pval nobs npar weighted
#> Class: integer numeric integer integer logical
#>
#> Name: method control
#> Class: character ControlEL
#>
#> Known Subclasses:
#> Class "SummaryGLM", directly
#> Class "SummaryQGLM", by class "SummaryGLM", distance 2
```