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TMB (version 1.7.22)

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

Description

With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.

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Version

Install

install.packages('TMB')

Monthly Downloads

29,002

Version

1.7.22

License

GPL-2

Issues

68

Pull Requests

4

Stars

187

Forks

85

Maintainer

Kasper Kristensen

Last Published

September 28th, 2021

Functions in TMB (1.7.22)

as.list.sdreport

Convert estimates to original list format.
FreeADFun

Free memory allocated on the C++ side by MakeADFun.
compile

Compile a C++ template to DLL suitable for MakeADFun.
config

Get or set internal configuration variables
plot.tmbprofile

Plot likelihood profile.
precompile

Precompile the TMB library in order to speed up compilation of templates.
MakeADFun

Construct objective functions with derivatives based on a compiled C++ template.
confint.tmbprofile

Profile based confidence intervals.
gdbsource

Source R-script through gdb to get backtrace.
dynlib

Add dynlib extension
oneStepPredict

Calculate one-step-ahead (OSA) residuals for a latent variable model.
print.sdreport

Print brief model summary
print.checkConsistency

Print output from checkConsistency
newtonOption

Set newton options for a model object.
openmp

Control number of openmp threads.
summary.sdreport

summary tables of model parameters
sdreport

General sdreport function.
template

Create cpp template to get started.
tmbprofile

Adaptive likelihood profiling.
tmbroot

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

Generalized newton optimizer.
runExample

Run one of the test examples.
runSymbolicAnalysis

Run symbolic analysis on sparse Hessian
normalize

Normalize process likelihood using the Laplace approximation.
summary.checkConsistency

Summarize output from checkConsistency
Rinterface

Create minimal R-code corresponding to a cpp template.
benchmark

Benchmark parallel templates
checkConsistency

Check consistency and Laplace accuracy