R2admb (version 0.7.16)

AIC.admb: 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 admb
AIC(object, ..., k = 2)
# S3 method for admb
confint(object, parm, level = 0.95, method = "default",
  type = "fixed", ...)
# S3 method for admb
print(x, verbose = FALSE, ...)
# S3 method for admb
summary(object, correlation = FALSE, symbolic.cor = FALSE,
  ...)
# S3 method for summary.admb
print(x, digits = max(3, getOption("digits") - 3),
  symbolic.cor = x$symbolic.cor,
  signif.stars = getOption("show.signif.stars"), ...)
# S3 method for admb
logLik(object, ...)
# S3 method for admb
coef(object, type = "fixed", ...)
# S3 method for admb
vcov(object, type = "fixed", ...)
stdEr(object, ...)
# S3 method for admb
stdEr(object, type = "fixed", ...)
# S3 method for 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

# NOT RUN {
 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)

# }