print.BinaryEPPM {BinaryEPPM}

Printing of BinaryEPPM Objects

Description

Prints objects of class "BinaryEPPM".

Usage

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

Arguments

x

fitted model object of class "BinaryEPPM".

digits

digits of printed output.

...

not currently used.

Value

An object of class "BinaryEPPM" is constructed. This object has the following attributes.

data.type

Indicator of the type of data either 0 "data.frame" or 1 "list".

list.data

Regardless of the "data.type", the data in list form.

call

The "call" to the function "BinaryEPPM".

formula

The model formula in "call".

model.type

The model type in "call".

model.name

The model name in "call".

link

The link function in "call".

covariates.matrix.p

The matrix of covariates for the model for p.

covariates.matrix.scalef

The matrix of covariates for the model for scale-factor.

offset.p

The vector of offsets for the model for p.

offset.scalef

The vector of offsets for the model for scale-factor.

coefficients

The coefficients of the fitted model.

loglik

The log-likelihood of the fitted model.

vcov

The variance-covariance matrix of the fitted model.

n

The number of observations. Relabelled duplication of "nobs" needed when calling function "lrtest".

nobs

The number of observations.

df.null

The degrees of freedom of the null model.

df.residual

The degrees of freedom of the residual model.

vnmax

Vector of number of "trials" in each observation.

weights

Vector of weights for observation.

converged

Indicator of convergence.

method

Method used to calculate pseudo.r.squared.

pseudo.r.squared

The value of the coefficient of determination r squared.

start

Initial estimates.

optim

Final model fit.

control

Control parameters for optimization function "optim".

fitted.values

The fitted values.

y

The dependent variable in the model.

terms

The terms in the model.

Author(s)

David M. Smith <[e-mail]>

References

Cribari-Neto F, Zeileis A. (2010). Beta Regression in R. Journal of Statistical Software, 34(2), 1-24. doi:10.18637/jss.v034.i02.

See Also

betareg

Examples

data("ropespores.case") 
BinaryEPPM(data = ropespores.case,
           number.spores / number.tested ~ 1 + offset(logdilution),
           model.type = 'p only', model.name = 'binomial')