miscmethods.mlogit: Methods for mlogit objects

In mlogit: Multinomial Logit Models

Description

Miscellaneous methods for mlogit objects.

Usage

## S3 method for class 'mlogit'
residuals(object, outcome = TRUE, ...)

## S3 method for class 'mlogit'
df.residual(object, ...)

## S3 method for class 'mlogit'
terms(x, ...)

## S3 method for class 'mlogit'
model.matrix(object, ...)

model.response.mlogit(object, ...)

## S3 method for class 'mlogit'
update(object, new, ...)

## S3 method for class 'mlogit'
print(
  x,
  digits = max(3, getOption("digits") - 2),
  width = getOption("width"),
  ...
)

## S3 method for class 'mlogit'
logLik(object, ...)

## S3 method for class 'mlogit'
summary(object, ..., type = c("chol", "cov", "cor"))

## S3 method for class 'summary.mlogit'
print(
  x,
  digits = max(3, getOption("digits") - 2),
  width = getOption("width"),
  ...
)

## S3 method for class 'mlogit'
index(x, ...)

## S3 method for class 'mlogit'
predict(object, newdata = NULL, returnData = FALSE, ...)

## S3 method for class 'mlogit'
fitted(
  object,
  type = c("outcome", "probabilities", "linpred", "parameters"),
  outcome = NULL,
  ...
)

## S3 method for class 'mlogit'
coef(
  object,
  subset = c("all", "iv", "sig", "sd", "sp", "chol"),
  fixed = FALSE,
  ...
)

## S3 method for class 'summary.mlogit'
coef(object, ...)

Arguments

outcome	a boolean which indicates, for the fitted and the residuals methods whether a matrix (for each choice, one value for each alternative) or a vector (for each choice, only a value for the alternative chosen) should be returned,
...	further arguments.
x, object	an object of class mlogit
new	an updated formula for the update method,
digits	the number of digits,
width	the width of the printing,
type	one of outcome (probability of the chosen alternative), probabilities (probabilities for all the alternatives), parameters for individual-level random parameters for the fitted method, how the correlated random parameters should be displayed : "chol" for the estimated parameters (the elements of the Cholesky decomposition matrix), "cov" for the covariance matrix and "cor" for the correlation matrix and the standard deviations,
newdata	a data.frame for the predict method,
returnData	for the predict method, if TRUE, the data is returned as an attribute,
subset	an optional vector of coefficients to extract for the coef method,
fixed	if FALSE (the default), constant coefficients are not returned,

mlogit documentation built on Feb. 28, 2020, 3:01 p.m.