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TMB (version 1.7.15)

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

1.7.15

License

GPL-2

Maintainer

Kasper Kristensen

Last Published

November 9th, 2018

Functions in TMB (1.7.15)

newton

Generalized newton optimizer.
newtonOption

Set newton options for a model object.
precompile

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

Print output from checkConsistency
sdreport

General sdreport function.
runSymbolicAnalysis

Run symbolic analysis on sparse Hessian
checkConsistency

Check consistency and Laplace accuracy
tmbroot

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

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

Normalize process likelihood using the Laplace approximation.
compile

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

Source R-script through gdb to get backtrace.
template

Create cpp template to get started.
tmbprofile

Adaptive likelihood profiling.
print.sdreport

Print brief model summary
runExample

Run one of the test examples.
summary.checkConsistency

Summarize output from checkConsistency
summary.sdreport

summary tables of model parameters
MakeADFun

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

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

Get or set internal configuration variables
confint.tmbprofile

Profile based confidence intervals.
dynlib

Add dynlib extension
as.list.sdreport

Convert estimates to original list format.
benchmark

Benchmark parallel templates
openmp

Control number of openmp threads.
plot.tmbprofile

Plot likelihood profile.