summary.cdfqr {cdfquantreg}

S3 Methods for getting output from fitted cdfqr Objects.

Description

Give the S3 Methods for CDF-Quantile Distribution Models

Usage

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

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

## S3 method for class 'cdfqr'
coef(object, type = "full", ...)

## S3 method for class 'cdfqr'
vcov(object, type = "full", ...)

## S3 method for class 'cdfqr'
update(object, formula., zero.fo., one.fo., mu.fo., ..., evaluate = TRUE)

## S3 method for class 'cdfqr'
confint(object, parm, level = 0.95, submodel = "full", ...)

## S3 method for class 'cdfqr'
formula(x, ...)

## S3 method for class 'cdfqr'
nobs(object, ...)

## S3 method for class 'cdfqr'
deviance(object, ...)

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

## S3 method for class 'cdfqrH'
confint(
  object,
  parm,
  level = 0.95,
  type = c("full", "mean", "sigma", "zero", "one"),
  ...
)

## S3 method for class 'cdfqrFT'
confint(object, parm, level = 0.95, submodel = "full", ...)

Arguments

...

Pass onto other functions or currently ignored

x, object

The fitted cdfqr model.

digits

Number of digits to be retained in printed output.

type, submodel

The parts of coefficients or variance-covariance matrix to be extracted.Can be "full", "mean",or "sigma".

formula.

Changes to the formula. See update.Formula for details.

zero.fo., one.fo., mu.fo.

Changes to the formulas for zero/one component for hurdle models, and for location submodel for finite-tailed models.

evaluate

If true evaluate the new updated model else return the call for the new model.

parm

a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.

level

the confidence level required.

Examples

data(cdfqrExampleData)
fit <- cdfquantreg(crc99 ~ vert | confl, 't2','t2', data = JurorData)

summary(fit)
print(fit)
logLik(fit)
coef(fit)
deviance(fit)
vcov(fit)
confint(fit)

#Update the model
fit2 <- update(fit, crc99 ~ vert*confl | confl)
summary(fit2)