"hhh4"
Objectsprint
and summary
methods there are also some standard
extraction methods defined for objects of class "hhh4"
resulting
from a call to hhh4
.## S3 method for class 'hhh4':
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'hhh4':
summary(object, maxEV = FALSE, ...)## S3 method for class 'hhh4':
coef(object, se = FALSE, reparamPsi = TRUE,
idx2Exp = NULL, amplitudeShift = FALSE, ...)
## S3 method for class 'hhh4':
fixef(object, ...)
## S3 method for class 'hhh4':
ranef(object, tomatrix = FALSE, ...)
## S3 method for class 'hhh4':
formula(x, ...)
## S3 method for class 'hhh4':
nobs(object, ...)
## S3 method for class 'hhh4':
logLik(object, ...)
## S3 method for class 'hhh4':
vcov(object, reparamPsi = TRUE,
idx2Exp = NULL, amplitudeShift = FALSE, ...)
## S3 method for class 'hhh4':
confint(object, parm, level = 0.95,
reparamPsi = TRUE, idx2Exp = NULL, amplitudeShift = FALSE, ...)
"hhh4"
.print
, summary
, fixef
and ranef
methods: arguments passed to coef
.
For the remaining methods: unused (argument of the generic).TRUE
(default), the overdispersion parameter from the
negative binomial distribution is transformed from internal scale (-log)
to standard scale, where zero corresponds to a Poisson distribution.addSeason2formula
) should be transformed
to an amplitude/shift formulation.FALSE
(default), the vector of
all random effects is returned (as used internally). However, for
random intercepts of type="car"
, the number of parameters is
one less than the number of regions and the indcoef
-method returns all estimated (regression)
parameters from a hhh4
model as proposed by Paul and
Held (2011).
If the model includes random effects, those can be extracted with
ranef
, whereas fixef
returns the fixed parameters. The formula
-method returns the formulae used for the
three log-linear predictors in a list with elements "ar"
,
"ne"
, and "end"
.
The nobs
-method returns the number of observations used
for model fitting.
The logLik
-method returns an object of class
"logLik"
with "df"
and "nobs"
attributes.
For a random effects model, the value of the penalized
log-likelihood at the MLE is returned, but degrees of freedom are
not available (NA_real_
).
As a consequence, AIC
and BIC
are only
well defined for models without random effects;
otherwise these functions return NA_real_
.
The vcov
-method returns the estimated
variance-covariance matrix of the regression parameters.
The estimated variance-covariance matrix of random effects is
available as object$Sigma
.
The confint
-method returns Wald-type confidence
intervals (assuming asymptotic normality).
plot
and update
methods
for fitted "hhh4"
models.