mhurdle.methods {mhurdle}

Methods for mhurdle fitted objects

Description

specific predict, fitted, coef, vcov, summary, ... for mhurdle objects. In particular, these methods enables to extract the several parts of the model

Usage

## S3 method for class 'mhurdle'
coef(
  object,
  which = c("all", "h1", "h2", "h3", "h4", "sd", "corr", "tr", "pos"),
  ...
)

## S3 method for class 'mhurdle'
vcov(
  object,
  which = c("all", "h1", "h2", "h3", "h4", "sd", "corr", "tr", "pos"),
  ...
)

## S3 method for class 'mhurdle'
logLik(object, naive = FALSE, ...)

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

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

## S3 method for class 'summary.mhurdle'
coef(
  object,
  which = c("all", "h1", "h2", "h3", "sd", "corr", "tr", "pos"),
  ...
)

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

## S3 method for class 'mhurdle'
fitted(object, which = c("all", "zero", "positive"), mean = FALSE, ...)

## S3 method for class 'mhurdle'
predict(object, newdata = NULL, what = c("E", "Ep", "p"), ...)

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

## S3 method for class 'mhurdle'
nobs(object, which = c("all", "null", "positive"), ...)

## S3 method for class 'mhurdle'
effects(
  object,
  covariate = NULL,
  data = NULL,
  what = c("E", "Ep", "p"),
  reflevel = NULL,
  mean = FALSE,
  ...
)

Arguments

object, x

an object of class "mhurdle",

which

which coefficients or covariances should be extracted ? Those of the selection ("h1"), consumption ("h2") or purchase ("h3") equation, the other coefficients "other" (the standard error and the coefficient of corr), the standard error ("sigma") or the coefficient of correlation ("rho"),

...

further arguments.

naive

a boolean, it TRUE, the likelihood of the naive model is returned,

digits

see print,

width

see print,

mean

if TRUE, the mean of the effects is returned,

newdata, data

a data.frame for which the predictions or the effectsshould be computed,

what

for the predict and the effects method, the kind of prediction, one of E Ep and p (respectively for expected values in the censored sample, expected values in the truncated sample and probability of positive values),

new

an updated formula for the update method,

covariate

the covariate for which the effect has to be computed,

reflevel

for the computation of effects for a factor, the reference level,