summary.addreg {addreg} | R Documentation |
Summarizing addreg Model Fits
Description
These functions are all methods
for class addreg
or summary.addreg
objects.
Usage
## S3 method for class 'addreg'
summary(object, correlation = FALSE, ...)
## S3 method for class 'summary.addreg'
print(x, digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"), ...)
Arguments
object |
an object of class |
x |
an object of class |
correlation |
logical; if |
digits |
the number of significant digits to use when printing. |
signif.stars |
logical; if |
... |
further arguments passed to or from other methods. |
Details
These perform the same function as summary.glm
and print.summary.glm
,
producing similar results for addreg
models. print.summary.addreg
additionally prints
the small-sample corrected AIC (aic.c
), the number of EM iterations for the parameterisation
corresponding to the MLE, and for negative binomial models, the estimate of (
scale
-1)
and its standard error.
The dispersion used in calculating standard errors is fixed as for binomial and Poisson
models, and is estimated via maximum likelihood for negative binomial models.
Value
summary.addreg
returns an object of class "summary.addreg"
, a list with components
call |
the component from |
family |
the component from |
deviance |
the component from |
aic |
the component from |
aic.c |
the component from |
df.residual |
the component from |
null.deviance |
the component from |
df.null |
the component from |
iter |
the component from |
deviance.resid |
the deviance residuals: see |
coefficients |
the matrix of coefficients, standard errors, z-values and p-values. |
aliased |
included for compatibility — always |
dispersion |
the inferred/estimated dispersion. |
df |
included for compatibility — a 3-vector of the number of coefficients, the number of residual degrees of freedom, and the number of coefficients (again). |
cov.unscaled |
the unscaled ( |
cov.scaled |
ditto, scaled by |
correlation |
if |
For negative binomial models, the object also contains
phi |
the estimate of |
var.phi |
the estimated variance of |
Note
If object$boundary == TRUE
, the standard errors of the coefficients
are not valid, and a matrix of NaN
s is returned by vcov.addreg
.
Author(s)
Mark W. Donoghoe markdonoghoe@gmail.com
See Also
Examples
## For an example, see example(addreg)