"hhh4" ObjectsBesides print and summary methods there are also some standard
extraction methods defined for objects of class "hhh4" resulting
from a call to hhh4.
The implementation is illustrated in Meyer et al. (2017, Section 5),
see vignette("hhh4_spacetime").
# S3 method for hhh4
print(x, digits = max(3, getOption("digits") - 3), ...)
# S3 method for hhh4
summary(object, maxEV = FALSE, ...)# S3 method for hhh4
coef(object, se = FALSE, reparamPsi = TRUE,
idx2Exp = NULL, amplitudeShift = FALSE, ...)
# S3 method for hhh4
fixef(object, ...)
# S3 method for hhh4
ranef(object, tomatrix = FALSE, intercept = FALSE, ...)
# S3 method for hhh4
coeflist(x, ...)
# S3 method for hhh4
formula(x, ...)
# S3 method for hhh4
nobs(object, ...)
# S3 method for hhh4
logLik(object, ...)
# S3 method for hhh4
vcov(object, reparamPsi = TRUE,
idx2Exp = NULL, amplitudeShift = FALSE, ...)
# S3 method for hhh4
confint(object, parm, level = 0.95,
reparamPsi = TRUE, idx2Exp = NULL, amplitudeShift = FALSE, ...)
# S3 method for hhh4
residuals(object, type = c("deviance", "pearson", "response"), ...)
The coef-method returns all estimated (regression)
parameters from a hhh4 model.
If the model includes random effects, those can be extracted with
ranef, whereas fixef returns the fixed parameters.
The coeflist-method extracts the model coefficients in a list
(by parameter group).
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$Sigma.
The confint-method returns Wald-type confidence
intervals (assuming asymptotic normality).
The residuals-method extracts raw ("response") or
"deviance" or standardized ("pearson")
residuals from the model fit similar to
residuals.glm for Poisson or NegBin GLM's.
Note that the squared Pearson residual is equivalent to the
normalized squared error score, which can be computed from the
fitted model using scores(object, "nses").
an object of class "hhh4".
the number of significant digits to use when printing parameter estimates.
logical indicating if the summary should contain the
(range of the) dominant eigenvalue as a measure of the importance of
the epidemic components. By default, the value is not calculated as
this may take some seconds depending on the number of time points
and units in object$stsObj.
For the print, summary, fixef, ranef,
and coeflist methods: arguments passed to coef.
For the remaining methods: unused (argument of the generic).
logical. If 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.
logical switch indicating if standard errors are required
integer vector selecting the parameters
which should be returned on exp-scale.
Alternatively, idx2Exp = TRUE will exp-transform all
parameters except for those associated with log() covariates
or already affected by reparamPsi or amplitudeShift.
logical switch indicating whether the parameters
for sine/cosine terms modelling seasonal patterns
(see addSeason2formula) should be transformed
to an amplitude/shift formulation.
logical. If 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 individual parameters are
not obviously linked to specific regions. Setting tomatrix to
TRUE returns a more useful representation of random effects
in a matrix with as many rows as there are regions and as many
columns as there are random effects. Here, any CAR-effects are
transformed to region-specific effects.
logical. If FALSE (default), the returned
random effects represent zero-mean deviations around the
corresponding global intercepts of the log-linear predictors.
Setting intercept=TRUE adds these global intercepts to the
result (and implies tomatrix=TRUE).
a vector of numbers or names, specifying which parameters are to be given confidence intervals. If missing, all parameters are considered.
the confidence level required.
the type of residuals which should be returned. The
alternatives are "deviance" (default), "pearson",
and "response".
Michaela Paul and Sebastian Meyer
Meyer, S., Held, L. and Höhle, M. (2017): Spatio-temporal analysis of epidemic phenomena using the R package surveillance. Journal of Statistical Software, 77 (11), 1-55. tools:::Rd_expr_doi("10.18637/jss.v077.i11")
the plot
and update methods
for fitted "hhh4" models.