-Class

[,numberedModelValuesAccessors-method

[&lt;-,numberedModelValuesAccessors-method

[,numberedObjects-method

[&lt;-,numberedObjects-method

[[,CNumericList-method

[[&lt;-,CNumericList-method

[[,RNumericList-method

[[&lt;-,RNumericList-method

[[,nimPointerList-method

[[&lt;-,nimPointerList-method

[[&lt;-,nimbleFunctionList-method

[,distributionsClass-method

[[,distributionsClass-method

[[,conjugacyRelationshipsClass-method

dsqrtinvgamma

rsqrtinvgamma

is.Cmodel

is.Cnf

is.Rmodel

is.model

samplesSummary

calc_dmnormConjugacyContributions

calc_dmnormAltParams

calc_dwishAltParams

calc_dcatConjugacyContributions

CAR_calcM

CAR_calcC

CAR_calcCmatrix

CAR_calcEVs2

CAR_calcEVs3

getNodeFunctionIndexedInfo

singleModelValuesAccess

getNimbleProject

cc_getNodesInExpr

nimbleInternalFunctions

nimbleUserNamespace

<p>Functions and classes used internally in NIMBLE and not expected to be called directly by users. Some functions and classes not intended for direct use are documented and/or exported because they are used within Reference Class methods for classes programmatically generated by NIMBLE.</p>

nimble-internal

A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++.  'NIMBLE' includes default methods for MCMC, particle filtering, Monte Carlo Expectation Maximization, and some other tools.  The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides.  'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code.  Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well.  A full User Manual is available at <https://r-nimble.org>.

nimble-internal: Functions and Classes Internal to NIMBLE

Description

Arguments