profilemethods  R Documentation 
Compute likelihood profiles for a fitted model
proffun(fitted, which = 1:p, maxsteps = 100, alpha = 0.01, zmax = sqrt(qchisq(1  alpha/2, p)), del = zmax/5, trace = FALSE, skiperrs=TRUE, std.err, tol.newmin = 0.001, debug=FALSE, prof.lower, prof.upper, skip.hessian = TRUE, continuation = c("none","naive","linear"), try_harder=FALSE, ...) ## S4 method for signature 'mle2' profile(fitted, ...)
fitted 
A fitted maximum likelihood model of class “mle2” 
which 
a numeric or character vector describing which parameters to profile (default is to profile all parameters) 
maxsteps 
maximum number of steps to take looking for an upper value of the negative loglikelihood 
alpha 
maximum (twosided) likelihood ratio test confidence level to find 
zmax 
maximum value of signed square root of deviance difference to find (default value corresponds to a 2tailed chisquared test at level alpha) 
del 
step size for profiling 
trace 
(logical) produce tracing output? 
skiperrs 
(logical) ignore errors produced during profiling? 
std.err 
Optional numeric vector of standard errors, for cases when the Hessian is badly behaved. Will be replicated if necessary, and NA values will be replaced by the corresponding values from the fit summary 
tol.newmin 
tolerance for diagnosing a new minimum below the minimum deviance estimated in initial fit is found 
debug 
(logical) debugging output? 
prof.lower 
optional vector of lower bounds for profiles 
prof.upper 
optional vector of upper bounds for profiles 
continuation 
use continuation method to set starting values?

skip.hessian 
skip hessian (defunct?) 
try_harder 
(logical) ignore 
... 
additional arguments (not used) 
proffun
is the guts of the profile method, exposed
so that other packages can use it directly.
See the vignette (vignette("mle2",package="bbmle")
)
for more technical details of how profiling is done.
profile.mleclass
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