| confint.glmmTMB {glmmTMB} | R Documentation |
Calculate confidence intervals
## S3 method for class 'glmmTMB'
confint(object, parm, level = 0.95, method = c("wald",
"Wald", "profile", "uniroot"), component = c("all", "cond", "zi", "other"),
estimate = TRUE, parallel = c("no", "multicore", "snow"),
ncpus = getOption("profile.ncpus", 1L), cl = NULL, ...)
object |
|
parm |
Specification of a parameter subset after
|
level |
Confidence level. |
method |
'wald', 'profile', or 'uniroot': see Details function) |
component |
Which of the three components 'cond', 'zi' or 'other' to select. Default is to select 'all'. |
estimate |
(logical) add a third column with estimate ? |
parallel |
method (if any) for parallel computation |
ncpus |
number of CPUs/cores to use for parallel computation |
cl |
cluster to use for parallel computation |
... |
arguments may be passed to |
Available methods are
These intervals are based on the standard errors calculated for parameters on the scale of their internal parameterization depending on the family. Derived quantities such as standard deviation parameters and dispersion parameters are backtransformed. It follows that confidence intervals for these derived quantities are asymmetric.
This method computes a likelihood profile
for the specified parameter(s) using profile.glmmTMB;
fits a spline function to each half of the profile; and
inverts the function to find the specified confidence interval.
This method uses the uniroot
function to find critical values of one-dimensional profile
functions for each specified parameter.
data(sleepstudy, package="lme4") model <- glmmTMB(Reaction ~ Days + (1|Subject), sleepstudy) confint(model) ## Not run: confint(model,parm=1,method="profile") ## End(Not run)