The LKJ Distribution for the Cholesky Factor of a Correlation Matrix
NIMBLE language function to break tracking of derivatives
Constraint calculations in NIMBLE
CnimbleFunctionBase-class
Class CnimbleFunctionBase
Placeholder for MCMCsuite
The Exponential Distribution
The Stick Breaking Function
The Multinomial Distribution
The Multivariate t Distribution
The Wishart Distribution
Interval calculations
The Dirichlet Distribution
Placeholder for buildLiuWestFilter
Placeholder for buildIteratedFilter2
Class MCMCconf
The Double Exponential (Laplace) Distribution
Check for interrupt (e.g. Ctrl-C) during nimbleFunction execution. Part of the NIMBLE language.
Clear compiled objects from a project and unload shared library
Get information about a distribution
Remove user-supplied distributions from use in NIMBLE BUGS models
The Inverse Gamma Distribution
Convert CAR structural parameters to adjacency, weights, num format
Automated parameter blocking procedure for efficient MCMC sampling
The Inverse Wishart Distribution
Determine if any values in a vector are NA or NaN
The Improper Uniform Distribution
Placeholder for buildAuxiliaryFilter
Calculate the lower bound for the autocorrelation parameter of the dcar_proper
distribution
Explicitly declare a variable in run-time code of a nimbleFunction
Calculate the upper bound for the autocorrelation parameter of the dcar_proper
distribution
Creates a nimbleFunction for executing the Metropolis-Hastings jumping decision,
and updating values in the model, or in a carbon copy modelValues object, accordingly.
Get value of bound of a stochastic node in a model
Build the MCMCconf object for construction of an MCMC object
Placeholder for buildEnsembleKF
compile NIMBLE models and nimbleFunctions
Placeholder for buildBootstrapFilter
Get the directory path to one of the classic BUGS examples installed with NIMBLE package
Create an Identity matrix (Deprecated)
Get nimbleFunction definition
Make an object of information about a model-bound pairing for getBound. Used internally
Laplace approximation
EXPERIMENTAL: Get list of parameter names generated by model macros
Set values of one variable of a modelValues object from an R matrix
Calculating WAIC using an offline algorithm
Class RmodelBaseClass
Convert weights vector to parameters of dcar_proper
distributio
Turn a numeric vector into a single-row or single-column matrix
The Multivariate Normal Distribution
Builds an MCEM algorithm from a given NIMBLE model
Placeholder for compareMCMCs
Class codeBlockClass
Create an MCMC object from a NIMBLE model, or an MCMC configuration object
EXPERIMENTAL: Turn a function into a model macro builder
A model macro expands one line of code in a nimbleModel into one or
more new lines. This supports compact programming by defining
re-usable modules. model_macro_builder
takes as input a
function that constructs new lines of model code from the original
line of code. It returns a function suitable for internal use by
nimbleModel
that arranges arguments for input function. Macros
are an experimental feature and are available only after setting
nimbleOptions(enableModelMacros = TRUE)
.
Halt execution of a nimbleFunction function method. Part of the NIMBLE language
access (call) a member function of a nimbleFunction
create a nimbleList
Singular Value Decomposition of a Matrix
Executes one or more chains of NIMBLE's default MCMC algorithm, for a model specified using BUGS code
check if a nimbleFunction
getConditionallyIndependentSets
Get a list of conditionally independent sets of nodes in a nimble model
Integration of One-Dimensional Functions
Create a list of nimbleFunctions
Creates matrix or array objects for use in nimbleFunctions
Copying function for NIMBLE
check if a nimbleList
Nimble Derivatives
create a virtual nimbleFunction, a base class for other nimbleFunctions
Automated transformations of model nodes to unconstrained scales
eigenNimbleList definition
Extract named elements from MCMC sampler control list
Creates a default control
argument for nimOptim
.
Power function for integer-valued exponent
nimble: MCMC, Particle Filtering, and Programmable Hierarchical Modeling
Mathematical functions for BUGS and nimbleFunction programming
Create a NIMBLE BUGS model from a variety of input formats, including BUGS model files
print function for use in nimbleFunctions
create a nimbleType object
Add user-supplied distributions for use in NIMBLE BUGS models
Make an R function callable from compiled nimbleFunctions (including nimbleModels).
calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model
Data type for the control
parameter of nimOptim
Performs initialization of nimble model node values and log probabilities
MCMC Sampling Algorithms
Creates numeric, integer or logical vectors for use in nimbleFunctions
Creates a nimbleFunction for setting the values of one or more model nodes,
calculating the associated deterministic dependents and logProb values,
and returning the total sum log-probability.
Spectral Decomposition of a Matrix
General-purpose Optimization
Create a NIMBLE modelValues Object
Information on initial values in a NIMBLE model
return sizes of an object whether it is a vector, matrix or array
waicDetailsNimbleList definition
The t Distribution
svdNimbleList definition
waicNimbleList definition
Resizes a modelValues object
Time execution of NIMBLE code
Tests BUGS examples in the NIMBLE system
valueInCompiledNimbleFunction
get or set value of member data from a compiled nimbleFunction using a multi-interface
Calculate bounds for the autocorrelation parameter of the dcar_proper
distribution
Makes the Metropolis-Hastings acceptance decision, based upon the input (log) Metropolis-Hastings ratio
Get NIMBLE Option
Configure Reversible Jump for Variable Selection
Make an object of information about a model-parameter pairing for getParam. Used internally
Information on model structure used for derivatives
Get value of a parameter of a stochastic node in a model
modelValuesBaseClass-class
Class modelValuesBaseClass
Returns number of rows of modelValues
Class for NIMBLE model definition
Get posterior samples for a Dirichlet process measure
Class modelBaseClass
Access or set a member variable of a nimbleFunction
Basic nimbleFunctions for calculate, simulate, and getLogProb with a set of nodes
Basic nimbleFunctions for using a NIMBLE model with sets of stored values
Explicitly declare objects created in setup code to be preserved and compiled as member data
Organize model nodes for marginalization
cat function for use in nimbleFunctions
NIMBLE language functions for R-like vector construction
Functions and Classes Internal to NIMBLE
Turn BUGS model code into an object for use in nimbleModel
or readBUGSmodel
Create a NIMBLE model from BUGS code
Create a nimbleFunction that wraps a call to external compiled code
Perform k-fold cross-validation on a NIMBLE model fit by MCMC
NIMBLE Options Settings
Run one or more chains of an MCMC algorithm and return samples, summary and/or WAIC
Creates a nimbleFunction for setting the value of a scalar model node,
calculating the associated deterministic dependents and logProb values,
and returning the total sum log-probability.
set the size of a numeric variable in NIMBLE
Access or set values for a set of nodes in a model
Create the confs for a custom NIMBLE modelValues object
Class nimbleFunctionBase
create a nimbleFunction
Creates a deafult control
argument for optim
(just an empty list). Print error messages after failed compilation
Data type for the return value of nimOptim
Generates a weighted sample (with replacement) of ranks
Using WAIC
singleVarAccessClass-class
Class singleVarAccessClass
Summarize results from Laplace approximation
Temporarily set some NIMBLE options.
Class CmodelBaseClass
BUGSdeclClass contains the information extracted from one BUGS declaration
Data type for the return value of nimDerivs
Calculate number of islands based on a CAR adjacency matrix.
The Chinese Restaurant Process Distribution
The CAR-Normal Distribution
The Categorical Distribution
create an ADproxyModelClass object
The CAR-Proper Distribution