EXPERIMENTAL Data type for the return value of nimDerivs
Create an MCMC function from a NIMBLE model, or an MCMC configuration object
Calculate bounds for the autocorrelation parameter of the dcar_proper
distribution
CnimbleFunctionBase-class
Class CnimbleFunctionBase
Constraint calculations in NIMBLE
Explicitly declare a variable in run-time code of a nimbleFunction
The CAR-Normal Distribution
Remove user-supplied distributions from use in NIMBLE BUGS models
The CAR-Proper Distribution
The Improper Uniform Distribution
The Inverse Gamma Distribution
Class MCMCsuiteClass
ModifiedRmmParseKeywords2
[[' = 'outputCppArrayIndex2',
The Inverse Wishart Distribution
Convert weights vector to parameters of dcar_proper
distributio
Get the directory path to one of the classic BUGS examples installed with NIMBLE package
make_MCMC_comparison_pages
Make html pages summarizing results from compareMCMCs
Turn a numeric vector into a single-row or single-column matrix
Create a bootstrap particle filter algorithm to estimate log-likelihood.
Calculate number of islands based on a CAR adjacency matrix.
Class modelBaseClass
The Chinese Restaurant Process Distribution
The Categorical Distribution
Create an Ensemble Kalman filter algorithm to sample from latent states.
Get information about a distribution
The Multinomial Distribution
The Multivariate t Distribution
Automated parameter blocking procedure for efficient MCMC sampling
Create an auxiliary particle filter algorithm to estimate log-likelihood.
check if a nimbleFunction
Build the MCMCconf object for construction of an MCMC object
compile NIMBLE models and nimbleFunctions
Print error messages after failed compilation
create a virtual nimbleFunction, a base class for other nimbleFunctions
create a nimbleList
check if a nimbleList
EXPERIMENTAL Data type for the return value of nimOptim
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)
.
reshape_comparison_results
Convert comparison results to a more general format
Returns number of rows of modelValues
Create an Identity matrix (Deprecated)
modelValuesBaseClass-class
Class modelValuesBaseClass
eigenNimbleList definition
Interval calculations
The Exponential Distribution
access (call) a member function of a nimbleFunction
Singular Value Decomposition of a Matrix
Calculate the upper bound for the autocorrelation parameter of the dcar_proper
distribution
The Wishart Distribution
Convert CAR structural parameters to adjacency, weights, num format
Resizes a modelValues object
Create the confs for a custom NIMBLE modelValues object
Class CmodelBaseClass
MCMC Sampling Algorithms
Calculate the lower bound for the autocorrelation parameter of the dcar_proper
distribution
The Multivariate Normal Distribution
return sizes of an object whether it is a vector, matrix or array
nimble
NIMBLE language functions for R-like vector construction
combine_MCMC_comparison_results
Combine multiple objects returned by compareMCMCs
Spectral Decomposition of a Matrix
Temporarily set some NIMBLE options.
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.
Class MCMCconf
Set values of one variable of a modelValues object from an R matrix
Functions and Classes Internal to NIMBLE
Executes multiple MCMC algorithms and organizes results.
Turn BUGS model code into an object for use in nimbleModel
or readBUGSmodel
Mathematical functions for BUGS and nimbleFunction programming
Class RmodelBaseClass
Create a Liu and West particle filter algorithm.
Check for interrupt (e.g. Ctrl-C) during nimbleFunction execution. Part of the NIMBLE language.
The Stick Breaking Function
Builds an MCEM algorithm from a given NIMBLE model
Run multiple MCMCs (packages or NIMBLE cases) for multiple models and return summary results
create a nimbleType object
Makes the Metropolis-Hastings acceptance decision, based upon the input (log) Metropolis-Hastings ratio
Get value of a parameter of a stochastic node in a model
calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model
Add user-supplied distributions for use in NIMBLE BUGS models
Creates a nimbleFunction for executing the Metropolis-Hastings jumping decision,
and updating values in the model, or in a carbon copy modelValues object, accordingly.
Class codeBlockClass
Get NIMBLE Option
Determine if any values in a vector are NA or NaN
return the namespace in which a nimbleFunction is being loaded
Performs initialization of nimble model node values and log probabilities
Get value of bound of a stochastic node in a model
Get posterior samples for a Dirichlet process measure
Get nimbleFunction definition
Copying function for NIMBLE
Access or set a member variable of a nimbleFunction
Make an object of information about a model-bound pairing for getBound. Used internally
Make an object of information about a model-parameter pairing for getParam. Used internally
cat function for use in nimbleFunctions
Class for NIMBLE model definition
Nimble Derivatives
Create a NIMBLE modelValues Object
Creates matrix or array objects for use in nimbleFunctions
print function for use in nimbleFunctions
Nimble wrapper around R's builtin optim
. rename_MCMC_comparison_method
Rename a method in an object returned by compareMCMCs
Tests BUGS examples in the NIMBLE system
The t Distribution
svdNimbleList definition
Creates numeric, integer or logical vectors for use in nimbleFunctions
Class nimbleFunctionBase
Create a list of nimbleFunctions
Creates a deafult control
argument for nimOptim
. updateMCMCcomparisonWithHighOrderESS
Re-estimate effective sample size from results of compareMCMCs
EXPERIMENTAL Data type for the control
parameter of nimOptim
Halt execution of a nimbleFunction function method. Part of the NIMBLE language
Creates a deafult control
argument for optim
(just an empty list). Generates a weighted sample (with replacement) of ranks
Create a nimbleFunction that wraps a call to external compiled code
Executes one or more chains of NIMBLE's default MCMC algorithm, for a model specified using BUGS code
create a nimbleFunction
Create a NIMBLE model from BUGS code
NIMBLE Options Settings
Make an R function callable from compiled nimbleFunctions (including nimbleModels).
Perform k-fold cross-validation on a NIMBLE model fit by MCMC
Time execution of NIMBLE code
Run one or more chains of an MCMC algorithm and return samples, summary and/or WAIC
Create a NIMBLE BUGS model from a variety of input formats, including BUGS model files
Basic nimbleFunctions for using a NIMBLE model with sets of stored values
singleVarAccessClass-class
Class singleVarAccessClass
samplerAssignmentRules-class
Class samplerAssignmentRules
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
Explicitly declare objects created in setup code to be preserved and compiled as member data
Basic nimbleFunctions for calculate, simulate, and getLogProb with a set of nodes
valueInCompiledNimbleFunction
get or set value of member data from a compiled nimbleFunction using a multi-interface
Access or set values for a set of nodes in a model
The Dirichlet Distribution
The Double Exponential (Laplace) Distribution
BUGSdeclClass contains the information extracted from one BUGS declaration