Package: TMB 1.9.25

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

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.

Authors:Kasper Kristensen [aut, cre, cph], Brad Bell [cph], Hans Skaug [ctb], Arni Magnusson [ctb], Casper Berg [ctb], Anders Nielsen [ctb], Martin Maechler [ctb], Theo Michelot [ctb], Mollie Brooks [ctb], Alex Forrence [ctb], Christoffer Moesgaard Albertsen [ctb], Cole Monnahan [ctb]

TMB_1.9.25.tar.gz
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TMB_1.9.25.tgz(r-4.6-x86_64)TMB_1.9.25.tgz(r-4.6-arm64)TMB_1.9.25.tgz(r-4.5-x86_64)TMB_1.9.25.tgz(r-4.5-arm64)
TMB_1.9.25.tar.gz(r-4.7-arm64)TMB_1.9.25.tar.gz(r-4.7-x86_64)TMB_1.9.25.tar.gz(r-4.6-arm64)TMB_1.9.25.tar.gz(r-4.6-x86_64)
TMB_1.9.25.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
TMB/json (API)

# Install 'TMB' in R:
install.packages('TMB', repos = c('https://kaskr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kaskr/adcomp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

15.66 score 195 stars 182 packages 2.8k scripts 61k downloads 24 mentions 30 exports 4 dependencies

Last updated from:1ac3a227eb. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK94
linux-devel-x86_64OK106
source / vignettesOK144
linux-release-arm64OK99
linux-release-x86_64OK110
macos-release-arm64OK143
macos-release-x86_64OK266
macos-oldrel-arm64OK105
macos-oldrel-x86_64OK220
windows-devel-arm64OK226
windows-devel-x86_64OK139
windows-release-arm64OK234
windows-release-x86_64OK121
windows-oldrel-x86_64OK96
wasm-releaseOK94

Exports:benchmarkcheckConsistencycompileconfigdynlibFreeADFungdbsourceMakeADFunnewtonnewtonOptionnormalizeoneStepPredictopenmpplot.parallelBenchmarkplot.tmbprofileprecompileprint.backtraceprint.checkConsistencyprint.sdreportRinterfacerunExamplerunSymbolicAnalysissdreportSRsummary.checkConsistencysummary.sdreporttemplateTMB.Versiontmbprofiletmbroot

Dependencies:latticeMatrixRcppRcppEigen

Readme and manuals

Help Manual

Help pageTopics
Convert estimates to original list format.as.list.sdreport
Benchmark parallel templatesbenchmark plot.parallelBenchmark
Check consistency and Laplace accuracycheckConsistency
Compile a C++ template to DLL suitable for MakeADFun.compile
Get or set internal configuration variablesconfig
Profile based confidence intervals.confint.tmbprofile
Add dynlib extensiondynlib
Free memory allocated on the C++ side by 'MakeADFun'.FreeADFun
Source R-script through gdb to get backtrace.gdbsource print.backtrace
Gauss Kronrod configurationGK
Construct objective functions with derivatives based on a compiled C++ template.MakeADFun
Generalized newton optimizer.newton
Set newton options for a model object.newtonOption
Normalize process likelihood using the Laplace approximation.normalize
Calculate one-step-ahead (OSA) residuals for a latent variable model.oneStepPredict
Control number of OpenMP threads used by a TMB model.openmp
Plot likelihood profile.plot.tmbprofile
Precompile the TMB library in order to speed up compilation of templates.precompile
Print output from 'checkConsistency'print.checkConsistency
Print brief model summaryprint.sdreport
Create minimal R-code corresponding to a cpp template.Rinterface
Run one of the test examples.runExample
Run symbolic analysis on sparse HessianrunSymbolicAnalysis
General sdreport function.sdreport
Sequential reduction configurationSR
Summarize output from 'checkConsistency'summary.checkConsistency
summary tables of model parameterssummary.sdreport
Create cpp template to get started.template
Version information on API and ABI.TMB.Version
Adaptive likelihood profiling.tmbprofile
Compute likelihood profile confidence intervals of a TMB object by root-findingtmbroot