R: Dispatching a summary function based on the class of the LHS...

summary_formula {ergm} | R Documentation

## Dispatching a summary function based on the class of the LHS of a formula.

### Description

The generic `summary_formula()` (note the underscore) expects a formula argument and will attempt to identify the class of the LHS of the formula and dispatch to the appropriate `summary_formula` method.

### Usage

    summary_formula(object, ..., basis = NULL)

    ## S3 method for class 'ergm'
    summary_formula(object, ..., basis = NULL)

    ## S3 method for class 'network.list'
    summary_formula(object, response = NULL, ...,
      basis = NULL)

    ## S3 method for class 'network'
    summary_formula(object, response = NULL, ...,
      basis = NULL)

    ## S3 method for class 'pending_update_network'
    summary_formula(object, response = NULL,
      ..., basis = NULL)

    ## S3 method for class 'matrix'
    summary_formula(object, response = NULL, ...,
      basis = NULL)

    ## Default S3 method:
    summary_formula(object, response = NULL, ...,
      basis = NULL)

### Arguments

`object` | A two-sided formula.
`...` | further arguments passed to or used by methods.
`basis` | Optional object of the same class as the LHS of the formula, substituted in place of the LHS.
`response` | Name of the edge attribute whose value is to be modeled. Defaults to `NULL` for simple presence or absence, modeled via binary ERGM terms. Passing anything but `NULL` uses valued ERGM terms.

### Value

A vector of statistics measured on the network.

### Methods (by class)

- `ergm`: an `ergm` fit method, extracting its model from the fit.

- `network.list`: a method for a `network.list` on the LHS of the formula.

- `network`: a method for a `network` on the LHS of the formula.

- `pending_update_network`: a method for the semi-internal `pending_update_network` on the LHS of the formula.

- `matrix`: a method for a `matrix` on the LHS of the formula.

- `default`: a fallback method.

### See Also

`ergm()`, `network()`, ergm-terms

`summary.ergm_model()`

### Examples

    #
    # Lets look at the Florentine marriage data
    #
    data(florentine)
    #
    # test the summary_formula function
    #
    summary(flomarriage ~ edges + kstar(2))
    m <- as.matrix(flomarriage)
    summary(m ~ edges)  # twice as large as it should be
    summary(m ~ edges, directed=FALSE) # Now it's correct

[Package ergm version 3.10.4 Index]