AIC.admb {R2admb} | R Documentation |
Standard accessor functions for ADMB model fits
Description
Extract standard information such as log-likelihood, AIC, coefficients, etc. from ADMB model fits
Usage
## S3 method for class 'admb'
AIC(object, ..., k = 2)
## S3 method for class 'admb'
confint(object, parm, level = 0.95, method = "default",
type = "fixed", ...)
## S3 method for class 'admb'
print(x, verbose = FALSE, ...)
## S3 method for class 'admb'
summary(object, correlation = FALSE, symbolic.cor = FALSE,
...)
## S3 method for class 'summary.admb'
print(x, digits = max(3, getOption("digits") - 3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
## S3 method for class 'admb'
logLik(object, ...)
## S3 method for class 'admb'
coef(object, type = "fixed", ...)
## S3 method for class 'admb'
vcov(object, type = "fixed", ...)
stdEr(object, ...)
## S3 method for class 'admb'
stdEr(object, type = "fixed", ...)
## S3 method for class 'admb'
deviance(object, ...)
Arguments
object |
an ADMB model fit (of class "admb") |
... |
other parameters (for S3 generic compatibility) |
k |
penalty value for AIC fits |
parm |
(currently ignored: FIXME) select parameters |
level |
alpha level for confidence interval |
method |
(character): "default" or "quad", quadratic (Wald) intervals based on approximate standard errors; "profile", profile CIs (if profile was computed); "quantile", CIs based on quantiles of the MCMC-generated posterior density (if MCMC was computed); "HPDinterval", CIs based on highest posterior density (ditto) |
type |
which type of parameters to report. Character vector, including one or more of "fixed" or "par" (standard, fixed-effect parameters); "random" (random effect parameters); "rep" (report variables); "sdrpt" (sdreport variables); "extra" (report and sdreport); "all" (all of the above). |
x |
an ADMB model fit (of class "admb") |
verbose |
show messages |
correlation |
currently unused parameter |
symbolic.cor |
currently unused parameter |
digits |
number of digits to display |
signif.stars |
show significance stars? |
Value
Extracts appropriate values: numeric (scalar) for AIC, type logLik for logLik, numeric vector of coefficients, numeric variance-covariance matrix of parameter estimates
Examples
admbex <- system.file("doc","Reedfrog_runs.RData",package="R2admb")
load(admbex)
m1
coef(m1)
summary(m1)
coef(summary(m1)) ## returns just z-table
AIC(m1)
vcov(m1)
logLik(m1)
deviance(m1)
stdEr(m1)