addMonitors |
Class 'MCMCconf' |
addMonitors2 |
Class 'MCMCconf' |
addSampler |
Class 'MCMCconf' |
ADNimbleList |
EXPERIMENTAL Data type for the return value of 'nimDerivs' |
AF_slice |
MCMC Sampling Algorithms |
all |
NIMBLE language functions for R-like vector construction |
any |
NIMBLE language functions for R-like vector construction |
any_na |
Determine if any values in a vector are NA or NaN |
any_nan |
Determine if any values in a vector are NA or NaN |
array |
Creates matrix or array objects for use in nimbleFunctions |
as.carAdjacency |
Convert CAR structural parameters to adjacency, weights, num format |
as.carCM |
Convert weights vector to parameters of 'dcar_proper' distributio |
asCol |
Turn a numeric vector into a single-row or single-column matrix |
asRow |
Turn a numeric vector into a single-row or single-column matrix |
autoBlock |
Automated parameter blocking procedure for efficient MCMC sampling |
dcar_normal |
The CAR-Normal Distribution |
dcar_proper |
The CAR-Proper Distribution |
dcat |
The Categorical Distribution |
dconstraint |
Constraint calculations in NIMBLE |
dCRP |
The Chinese Restaurant Process Distribution |
ddexp |
The Double Exponential (Laplace) Distribution |
ddirch |
The Dirichlet Distribution |
decide |
Makes the Metropolis-Hastings acceptance decision, based upon the input (log) Metropolis-Hastings ratio |
decideAndJump |
Creates a nimbleFunction for executing the Metropolis-Hastings jumping decision, and updating values in the model, or in a carbon copy modelValues object, accordingly. |
declare |
Explicitly declare a variable in run-time code of a nimbleFunction |
deregisterDistributions |
Remove user-supplied distributions from use in NIMBLE BUGS models |
dexp_nimble |
The Exponential Distribution |
dflat |
The Improper Uniform Distribution |
dhalfflat |
The Improper Uniform Distribution |
diag |
NIMBLE language functions for R-like vector construction |
dim |
return sizes of an object whether it is a vector, matrix or array |
dinterval |
Interval calculations |
dinvgamma |
The Inverse Gamma Distribution |
dinvwish_chol |
The Inverse Wishart Distribution |
Dirichlet |
The Dirichlet Distribution |
dirichlet |
The Dirichlet Distribution |
distributionInfo |
Get information about a distribution |
dmnorm_chol |
The Multivariate Normal Distribution |
dmulti |
The Multinomial Distribution |
dmvt_chol |
The Multivariate t Distribution |
Double-Exponential |
The Double Exponential (Laplace) Distribution |
DPmeasure |
MCMC Sampling Algorithms |
dsqrtinvgamma |
Functions and Classes Internal to NIMBLE |
dt_nonstandard |
The t Distribution |
dwish_chol |
The Wishart Distribution |
icloglog |
Mathematical functions for BUGS and nimbleFunction programming |
identityMatrix |
Create an Identity matrix (Deprecated) |
ilogit |
Mathematical functions for BUGS and nimbleFunction programming |
initializeInfo |
Class 'modelBaseClass' |
initializeModel |
Performs initialization of nimble model node values and log probabilities |
inprod |
Mathematical functions for BUGS and nimbleFunction programming |
integer |
Creates numeric, integer or logical vectors for use in nimbleFunctions |
Interval |
Interval calculations |
inverse |
Mathematical functions for BUGS and nimbleFunction programming |
Inverse-Gamma |
The Inverse Gamma Distribution |
Inverse-Wishart |
The Inverse Wishart Distribution |
inverse-wishart |
The Inverse Wishart Distribution |
iprobit |
Mathematical functions for BUGS and nimbleFunction programming |
is.Cmodel |
Functions and Classes Internal to NIMBLE |
is.Cnf |
Functions and Classes Internal to NIMBLE |
is.model |
Functions and Classes Internal to NIMBLE |
is.na |
NIMBLE language functions for R-like vector construction |
is.nan |
NIMBLE language functions for R-like vector construction |
is.nf |
check if a nimbleFunction |
is.nfGenerator |
Functions and Classes Internal to NIMBLE |
is.nl |
check if a nimbleList |
is.Rmodel |
Functions and Classes Internal to NIMBLE |
isBinary |
Class 'modelBaseClass' |
isData |
Class 'modelBaseClass' |
isDeterm |
Class 'modelBaseClass' |
isDiscrete |
Class 'modelBaseClass' |
isEndNode |
Class 'modelBaseClass' |
isMultivariate |
Class 'modelBaseClass' |
isStoch |
Class 'modelBaseClass' |
isTruncated |
Class 'modelBaseClass' |
isUnivariate |
Class 'modelBaseClass' |
isUserDefined |
Get information about a distribution |
makeBoundInfo |
Make an object of information about a model-bound pairing for getBound. Used internally |
makeParamInfo |
Make an object of information about a model-parameter pairing for getParam. Used internally |
matrix |
Creates matrix or array objects for use in nimbleFunctions |
MCMCconf |
Class 'MCMCconf' |
MCMCconf-class |
Class 'MCMCconf' |
MCMCsuite |
Placeholder for MCMCsuite |
modelBaseClass |
Class 'modelBaseClass' |
modelBaseClass-class |
Class 'modelBaseClass' |
modelDefClass |
Class for NIMBLE model definition |
modelDefClass-class |
Class for NIMBLE model definition |
modelInitialization |
Information on initial values in a NIMBLE model |
modelValues |
Create a NIMBLE modelValues Object |
modelValuesBaseClass |
Class 'modelValuesBaseClass' |
modelValuesBaseClass-class |
Class 'modelValuesBaseClass' |
modelValuesConf |
Create the confs for a custom NIMBLE modelValues object |
model_macro_builder |
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)'. |
Multinomial |
The Multinomial Distribution |
multinomial |
The Multinomial Distribution |
Multivariate-t |
The Multivariate t Distribution |
multivariate-t |
The Multivariate t Distribution |
MultivariateNormal |
The Multivariate Normal Distribution |
mvt |
The Multivariate t Distribution |
newModel |
Class 'modelBaseClass' |
nfMethod |
access (call) a member function of a nimbleFunction |
nfVar |
Access or set a member variable of a nimbleFunction |
nfVar<- |
Access or set a member variable of a nimbleFunction |
nf_preProcessMemberDataObject |
Functions and Classes Internal to NIMBLE |
nimArray |
Creates matrix or array objects for use in nimbleFunctions |
nimble |
nimble |
nimble-R-functions |
NIMBLE language functions for R-like vector construction |
nimbleCode |
Turn BUGS model code into an object for use in 'nimbleModel' or 'readBUGSmodel' |
nimbleExternalCall |
Create a nimbleFunction that wraps a call to external compiled code |
nimbleFunction |
create a nimbleFunction |
nimbleFunctionBase |
Class 'nimbleFunctionBase' |
nimbleFunctionBase-class |
Class 'nimbleFunctionBase' |
nimbleFunctionList |
Create a list of nimbleFunctions |
nimbleFunctionList-class |
Create a list of nimbleFunctions |
nimbleFunctionVirtual |
create a virtual nimbleFunction, a base class for other nimbleFunctions |
nimbleInternalFunctions |
Functions and Classes Internal to NIMBLE |
nimbleList |
create a nimbleList |
nimbleMCMC |
Executes one or more chains of NIMBLE's default MCMC algorithm, for a model specified using BUGS code |
nimbleModel |
Create a NIMBLE model from BUGS code |
nimbleOptions |
NIMBLE Options Settings |
nimbleRcall |
Make an R function callable from compiled nimbleFunctions (including nimbleModels). |
nimbleType |
create a nimbleType object |
nimbleType-class |
create a nimbleType object |
nimbleUserNamespace |
Functions and Classes Internal to NIMBLE |
nimC |
NIMBLE language functions for R-like vector construction |
nimCat |
cat function for use in nimbleFunctions |
nimCopy |
Copying function for NIMBLE |
nimDerivs |
Nimble Derivatives |
nimDim |
return sizes of an object whether it is a vector, matrix or array |
nimEigen |
Spectral Decomposition of a Matrix |
nimEquals |
Mathematical functions for BUGS and nimbleFunction programming |
nimInteger |
Creates numeric, integer or logical vectors for use in nimbleFunctions |
nimLogical |
Creates numeric, integer or logical vectors for use in nimbleFunctions |
nimMatrix |
Creates matrix or array objects for use in nimbleFunctions |
nimNumeric |
Creates numeric, integer or logical vectors for use in nimbleFunctions |
nimOptim |
Nimble wrapper around R's builtin 'optim'. |
nimOptimDefaultControl |
Creates a deafult 'control' argument for 'nimOptim'. |
nimPrint |
print function for use in nimbleFunctions |
nimRep |
NIMBLE language functions for R-like vector construction |
nimRound |
Mathematical functions for BUGS and nimbleFunction programming |
nimSeq |
NIMBLE language functions for R-like vector construction |
nimStep |
Mathematical functions for BUGS and nimbleFunction programming |
nimStop |
Halt execution of a nimbleFunction function method. Part of the NIMBLE language |
nimSvd |
Singular Value Decomposition of a Matrix |
nimSwitch |
Mathematical functions for BUGS and nimbleFunction programming |
nodeFunctions |
calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model |
numeric |
Creates numeric, integer or logical vectors for use in nimbleFunctions |
sampler |
MCMC Sampling Algorithms |
samplers |
MCMC Sampling Algorithms |
sampler_AF_slice |
MCMC Sampling Algorithms |
sampler_BASE |
MCMC Sampling Algorithms |
sampler_binary |
MCMC Sampling Algorithms |
sampler_CAR_normal |
MCMC Sampling Algorithms |
sampler_CAR_proper |
MCMC Sampling Algorithms |
sampler_categorical |
MCMC Sampling Algorithms |
sampler_crossLevel |
MCMC Sampling Algorithms |
sampler_CRP |
MCMC Sampling Algorithms |
sampler_CRP_concentration |
MCMC Sampling Algorithms |
sampler_ess |
MCMC Sampling Algorithms |
sampler_posterior_predictive |
MCMC Sampling Algorithms |
sampler_posterior_predictive_branch |
MCMC Sampling Algorithms |
sampler_RJ_fixed_prior |
MCMC Sampling Algorithms |
sampler_RJ_indicator |
MCMC Sampling Algorithms |
sampler_RJ_toggled |
MCMC Sampling Algorithms |
sampler_RW |
MCMC Sampling Algorithms |
sampler_RW_block |
MCMC Sampling Algorithms |
sampler_RW_dirichlet |
MCMC Sampling Algorithms |
sampler_RW_llFunction |
MCMC Sampling Algorithms |
sampler_RW_llFunction_block |
MCMC Sampling Algorithms |
sampler_RW_multinomial |
MCMC Sampling Algorithms |
sampler_RW_wishart |
MCMC Sampling Algorithms |
sampler_slice |
MCMC Sampling Algorithms |
samplesSummary |
Functions and Classes Internal to NIMBLE |
seq |
NIMBLE language functions for R-like vector construction |
seq_along |
NIMBLE language functions for R-like vector construction |
setAndCalculate |
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. |
setAndCalculateDiff |
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. |
setAndCalculateOne |
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. |
setData |
Class 'modelBaseClass' |
setInits |
Class 'modelBaseClass' |
setMonitors |
Class 'MCMCconf' |
setMonitors2 |
Class 'MCMCconf' |
setSamplerExecutionOrder |
Class 'MCMCconf' |
setSamplers |
Class 'MCMCconf' |
setSize |
set the size of a numeric variable in NIMBLE |
setThin |
Class 'MCMCconf' |
setThin2 |
Class 'MCMCconf' |
setupOutputs |
Explicitly declare objects created in setup code to be preserved and compiled as member data |
simNodes |
Basic nimbleFunctions for calculate, simulate, and getLogProb with a set of nodes |
simNodesMV |
Basic nimbleFunctions for using a NIMBLE model with sets of stored values |
simulate |
calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model |
singleModelValuesAccess |
Functions and Classes Internal to NIMBLE |
singleVarAccessClass |
Class 'singleVarAccessClass' |
singleVarAccessClass-class |
Class 'singleVarAccessClass' |
slice |
MCMC Sampling Algorithms |
stickbreaking |
The Stick Breaking Function |
StickBreakingFunction |
The Stick Breaking Function |
stick_breaking |
The Stick Breaking Function |
stop |
Halt execution of a nimbleFunction function method. Part of the NIMBLE language |
svd |
Singular Value Decomposition of a Matrix |
svdNimbleList |
svdNimbleList definition |