Template Model Builder: A General Random Effect Tool Inspired by ADMB

Documentation for package ‘TMB’ version 1.6.6

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benchmark	Benchmark parallel templates
compile	Compile a C++ template to DLL suitable for MakeADFun.
config	Get or set internal configuration variables
confint.tmbprofile	Profile based confidence intervals.
dynlib	Add dynlib extension
gdbsource	Source R-script through gdb to get backtrace.
MakeADFun	Construct objective functions with derivatives based on a compiled C++ template.
mcmc	MCMC sampling of TMB models
mcmc.hmc	[BETA VERSION] Draw MCMC samples from a model posterior using a Hamiltonian sampler.
mcmc.nuts	[BETA VERSION] Draw MCMC samples from a model posterior using the No-U-Turn (NUTS) sampler with dual averaging.
mcmc.rwm	[BETA VERSION] Draw MCMC samples from a model posterior using a Random Walk Metropolis (RWM) sampler.
newton	Generalized newton optimizer.
newtonOption	Set newton options for a model object.
oneStepPredict	Calculate one-step-ahead (OSA) residuals for a latent variable model.
openmp	Control number of openmp threads.
plot.parallelBenchmark	Benchmark parallel templates
plot.tmbprofile	Plot likelihood profile.
precompile	Precompile the TMB library in order to speed up compilation of templates.
print.backtrace	Source R-script through gdb to get backtrace.
print.sdreport	Print brief model summary
Rinterface	Create minimal R-code corresponding to a cpp template.
runExample	Run one of the test examples.
runSymbolicAnalysis	Run symbolic analysis on sparse Hessian
sdreport	General sdreport function.
summary.sdreport	summary tables of model parameters
template	Create cpp template to get started.
tmbprofile	Adaptive likelihood profiling.