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TMB (version 1.9.6)

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

30,820

Version

1.9.6

License

GPL-2

Issues

68

Pull Requests

4

Stars

187

Forks

85

Maintainer

Kasper Kristensen

Last Published

August 11th, 2023

Functions in TMB (1.9.6)

dynlib

Add dynlib extension
plot.tmbprofile

Plot likelihood profile.
precompile

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

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

Adaptive likelihood profiling.
print.sdreport

Print brief model summary
runSymbolicAnalysis

Run symbolic analysis on sparse Hessian
runExample

Run one of the test examples.
print.checkConsistency

Print output from checkConsistency
summary.sdreport

summary tables of model parameters
template

Create cpp template to get started.
sdreport

General sdreport function.
summary.checkConsistency

Summarize output from checkConsistency
GK

Gauss Kronrod configuration
compile

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

Benchmark parallel templates
checkConsistency

Check consistency and Laplace accuracy
FreeADFun

Free memory allocated on the C++ side by MakeADFun.
as.list.sdreport

Convert estimates to original list format.
config

Get or set internal configuration variables
SR

Sequential reduction configuration
Rinterface

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

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

Set newton options for a model object.
openmp

Control number of OpenMP threads used by a TMB model.
oneStepPredict

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

Profile based confidence intervals.
normalize

Normalize process likelihood using the Laplace approximation.
gdbsource

Source R-script through gdb to get backtrace.
newton

Generalized newton optimizer.