tmbroot: Compute likelihood profile confidence intervals of a TMB...

tmbrootR Documentation

Compute likelihood profile confidence intervals of a TMB object by root-finding


Compute likelihood profile confidence intervals of a TMB object by root-finding in contrast to tmbprofile, which tries to compute somewhat equally spaced values along the likelihood profile (which is useful for visualizing the shape of the likelihood surface), and then (via confint.tmbprofile) extracting a critical value by linear interpolation,


tmbroot(obj, name, target = 0.5 * qchisq(0.95, df = 1), lincomb,
  parm.range = c(NA, NA), sd.range = 7, trace = FALSE,
  continuation = FALSE)



Object from MakeADFun that has been optimized.


Name or index of a parameter to profile.


desired deviation from minimum log-likelihood. Default is set to retrieve the 95 if the objective function is a negative log-likelihood function


Optional linear combination of parameters to profile. By default a unit vector corresponding to name.


lower and upper limits; if NA, a value will be guessed based on the parameter value and sd.range


in the absence of explicit parm.range values, the range chosen will be the parameter value plus or minus sd.range times the corresponding standard deviation. May be specified as a two-element vector for different ranges below and above the parameter value.


report information?


use continuation method, i.e. set starting parameters for non-focal parameters to solutions from previous fits?


a two-element numeric vector containing the lower and upper limits (or NA if the target is not achieved in the range), with an attribute giving the total number of function iterations used


## Not run: 
runExample("simple",thisR=TRUE) <- tmbroot(obj,"logsd0")

## End(Not run)

TMB documentation built on Aug. 17, 2022, 1:16 a.m.

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