summary.addreg {addreg} | R Documentation |
These functions are all methods
for class addreg
or summary.addreg
objects.
## 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"), ...)
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. |
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 φ (scale
-1)
and its standard error.
The dispersion used in calculating standard errors is fixed as 1 for binomial and Poisson models, and is estimated via maximum likelihood for negative binomial models.
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 φ ( |
var.phi |
the estimated variance of |
If object$boundary == TRUE
, the standard errors of the coefficients
are not valid, and a matrix of NaN
s is returned by vcov.addreg
.
Mark W. Donoghoe markdonoghoe@gmail.com
## For an example, see example(addreg)