A B C D E F G H I L M N O P Q R S T U V W misc
nimble-package | nimble |
addMonitors | Class 'MCMCconf' |
addMonitors2 | Class 'MCMCconf' |
addRule | Class 'samplerAssignmentRules' |
addSampler | Class 'MCMCconf' |
ADNimbleList | EXPERIMENTAL Data type for the return value of 'nimDerivs' |
AF_slice | MCMC Sampling Algorithms |
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 |
besselK | Mathematical functions for BUGS and nimbleFunction programming |
BUGSdeclClass | BUGSdeclClass contains the information extracted from one BUGS declaration |
BUGSdeclClass-class | BUGSdeclClass contains the information extracted from one BUGS declaration |
buildAuxiliaryFilter | Create an auxiliary particle filter algorithm to estimate log-likelihood. |
buildBootstrapFilter | Create a bootstrap particle filter algorithm to estimate log-likelihood. |
buildEnsembleKF | Create an Ensemble Kalman filter algorithm to sample from latent states. |
buildLiuWestFilter | Create a Liu and West particle filter algorithm. |
buildMCEM | Builds an MCEM algorithm from a given NIMBLE model |
buildMCMC | Create an MCMC function from a NIMBLE model, or an MCMC configuration object |
c | NIMBLE language functions for R-like vector construction |
calcNodes | Basic nimbleFunctions for calculate, simulate, and getLogProb with a set of nodes |
calcNodesMV | Basic nimbleFunctions for using a NIMBLE model with sets of stored values |
calculate | calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model |
calculateDiff | calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model |
calc_dcatConjugacyContributions | Functions and Classes Internal to NIMBLE |
calc_dmnormAltParams | Functions and Classes Internal to NIMBLE |
calc_dmnormConjugacyContributions | Functions and Classes Internal to NIMBLE |
calc_dwishAltParams | Functions and Classes Internal to NIMBLE |
CAR-Normal | The CAR-Normal Distribution |
CAR-Proper | The CAR-Proper Distribution |
carBounds | Calculate bounds for the autocorrelation parameter of the 'dcar_proper' distribution |
carMaxBound | Calculate the upper bound for the autocorrelation parameter of the 'dcar_proper' distribution |
carMinBound | Calculate the lower bound for the autocorrelation parameter of the 'dcar_proper' distribution |
CAR_calcC | Functions and Classes Internal to NIMBLE |
CAR_calcCmatrix | Functions and Classes Internal to NIMBLE |
CAR_calcEVs2 | Functions and Classes Internal to NIMBLE |
CAR_calcEVs3 | Functions and Classes Internal to NIMBLE |
CAR_calcM | Functions and Classes Internal to NIMBLE |
CAR_calcNumIslands | Calculate number of islands based on a CAR adjacency matrix. |
cat | cat function for use in nimbleFunctions |
Categorical | The Categorical Distribution |
cc_getNodesInExpr | Functions and Classes Internal to NIMBLE |
checkConjugacy | Class 'modelBaseClass' |
checkInterrupt | Check for interrupt (e.g. Ctrl-C) during nimbleFunction execution. Part of the NIMBLE language. |
ChineseRestaurantProcess | The Chinese Restaurant Process Distribution |
cloglog | Mathematical functions for BUGS and nimbleFunction programming |
CmodelBaseClass | Class 'CmodelBaseClass' |
CmodelBaseClass-class | Class 'CmodelBaseClass' |
CnimbleFunctionBase | Class 'CnimbleFunctionBase' |
CnimbleFunctionBase-class | Class 'CnimbleFunctionBase' |
codeBlockClass | Class 'codeBlockClass' |
codeBlockClass-class | Class 'codeBlockClass' |
combine_MCMC_comparison_results | Combine multiple objects returned by compareMCMCs |
compareMCMCs | Run multiple MCMCs (packages or NIMBLE cases) for multiple models and return summary results |
compileNimble | compile NIMBLE models and nimbleFunctions |
configureMCMC | Build the MCMCconf object for construction of an MCMC object |
Constraint | Constraint calculations in NIMBLE |
copy | Copying function for NIMBLE |
crossLevel | MCMC Sampling Algorithms |
CRP | MCMC Sampling Algorithms |
CRP_concentration | MCMC Sampling Algorithms |
cube | Mathematical functions for BUGS and nimbleFunction programming |
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 |
eigen | Spectral Decomposition of a Matrix |
eigenNimbleList | eigenNimbleList definition |
expandNodeNames | Class 'modelBaseClass' |
expit | Mathematical functions for BUGS and nimbleFunction programming |
Exponential | The Exponential Distribution |
flat | The Improper Uniform Distribution |
getBound | Get value of bound of a stochastic node in a model |
getBUGSexampleDir | Get the directory path to one of the classic BUGS examples installed with NIMBLE package |
getCode | Class 'modelBaseClass' |
getDefinition | Get nimbleFunction definition |
getDependencies | Class 'modelBaseClass' |
getDependenciesList | Class 'modelBaseClass' |
getDimension | Class 'modelBaseClass' |
getDistribution | Class 'modelBaseClass' |
getDistributionInfo | Get information about a distribution |
getDownstream | Class 'modelBaseClass' |
getLoadingNamespace | return the namespace in which a nimbleFunction is being loaded |
getLogProb | calculate, calculateDiff, simulate, or get the current log probabilities (densities) a set of nodes in a NIMBLE model |
getLogProbNodes | Basic nimbleFunctions for calculate, simulate, and getLogProb with a set of nodes |
getLogProbNodesMV | Basic nimbleFunctions for using a NIMBLE model with sets of stored values |
getMonitors | Class 'MCMCconf' |
getMonitors2 | Class 'MCMCconf' |
getNimbleOption | Get NIMBLE Option |
getNimbleProject | Functions and Classes Internal to NIMBLE |
getNodeFunctionIndexedInfo | Functions and Classes Internal to NIMBLE |
getNodeNames | Class 'modelBaseClass' |
getParam | Get value of a parameter of a stochastic node in a model |
getParamNames | Get information about a distribution |
getSamplerExecutionOrder | Class 'MCMCconf' |
getSamplers | Class 'MCMCconf' |
getSamplesDPmeasure | Get posterior samples for a Dirichlet process measure |
getsize | Returns number of rows of modelValues |
getType | Get information about a distribution |
getVarNames | Class 'modelBaseClass' |
halfflat | The Improper Uniform 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.vec | Determine if any values in a vector are NA or NaN |
is.nan.vec | Determine if any values in a vector are NA or NaN |
is.nf | check if a nimbleFunction |
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 |
length | NIMBLE language functions for R-like vector construction |
logdet | Mathematical functions for BUGS and nimbleFunction programming |
logfact | Mathematical functions for BUGS and nimbleFunction programming |
loggam | Mathematical functions for BUGS and nimbleFunction programming |
logical | Creates numeric, integer or logical vectors for use in nimbleFunctions |
logit | Mathematical functions for BUGS and nimbleFunction programming |
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 |
make_MCMC_comparison_pages | Make html pages summarizing results from compareMCMCs |
matrix | Creates matrix or array objects for use in nimbleFunctions |
MCMCconf | Class 'MCMCconf' |
MCMCconf-class | Class 'MCMCconf' |
MCMCsuite | Executes multiple MCMC algorithms and organizes results. |
MCMCsuiteClass | Class 'MCMCsuiteClass' |
MCMCsuiteClass-class | Class 'MCMCsuiteClass' |
modelBaseClass | Class 'modelBaseClass' |
modelBaseClass-class | Class 'modelBaseClass' |
modelDefClass | Class for NIMBLE model definition |
modelDefClass-class | Class for NIMBLE model definition |
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)'. |
ModifiedRmmParseKeywords2 | [[' = 'outputCppArrayIndex2', |
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 |
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 |
optimControlNimbleList | EXPERIMENTAL Data type for the 'control' parameter of 'nimOptim' |
optimDefaultControl | Creates a deafult 'control' argument for 'optim' (just an empty list). |
optimResultNimbleList | EXPERIMENTAL Data type for the return value of 'nimOptim' |
pdexp | The Double Exponential (Laplace) Distribution |
pexp_nimble | The Exponential Distribution |
phi | Mathematical functions for BUGS and nimbleFunction programming |
pinvgamma | The Inverse Gamma Distribution |
posterior_predictive | MCMC Sampling Algorithms |
pow | Mathematical functions for BUGS and nimbleFunction programming |
pqDefined | Get information about a distribution |
print function for use in nimbleFunctions | |
printErrors | Print error messages after failed compilation |
printMonitors | Class 'MCMCconf' |
printRules | Class 'samplerAssignmentRules' |
printSamplers | Class 'MCMCconf' |
probit | Mathematical functions for BUGS and nimbleFunction programming |
pt_nonstandard | The t Distribution |
qdexp | The Double Exponential (Laplace) Distribution |
qexp_nimble | The Exponential Distribution |
qinvgamma | The Inverse Gamma Distribution |
qt_nonstandard | The t Distribution |
rankSample | Generates a weighted sample (with replacement) of ranks |
rcar_normal | The CAR-Normal Distribution |
rcar_proper | The CAR-Proper Distribution |
rcat | The Categorical Distribution |
rconstraint | Constraint calculations in NIMBLE |
rCRP | The Chinese Restaurant Process Distribution |
rdexp | The Double Exponential (Laplace) Distribution |
rdirch | The Dirichlet Distribution |
readBUGSmodel | Create a NIMBLE BUGS model from a variety of input formats, including BUGS model files |
registerDistributions | Add user-supplied distributions for use in NIMBLE BUGS models |
removeSamplers | Class 'MCMCconf' |
rename_MCMC_comparison_method | Rename a method in an object returned by compareMCMCs |
reorder | Class 'samplerAssignmentRules' |
rep | NIMBLE language functions for R-like vector construction |
resetData | Class 'modelBaseClass' |
resetMonitors | Class 'MCMCconf' |
reshape_comparison_results | Convert comparison results to a more general format |
resize | Resizes a modelValues object |
rexp_nimble | The Exponential Distribution |
rflat | The Improper Uniform Distribution |
rhalfflat | The Improper Uniform Distribution |
rinterval | Interval calculations |
rinvgamma | The Inverse Gamma Distribution |
rinvwish_chol | The Inverse Wishart Distribution |
Rmatrix2mvOneVar | Set values of one variable of a modelValues object from an R matrix |
rmnorm_chol | The Multivariate Normal Distribution |
RmodelBaseClass | Class 'RmodelBaseClass' |
RmodelBaseClass-class | Class 'RmodelBaseClass' |
rmulti | The Multinomial Distribution |
rmvt_chol | The Multivariate t Distribution |
rsqrtinvgamma | Functions and Classes Internal to NIMBLE |
rt_nonstandard | The t Distribution |
run.time | Time execution of NIMBLE code |
runCrossValidate | Perform k-fold cross-validation on a NIMBLE model fit by MCMC |
runMCMC | Run one or more chains of an MCMC algorithm and return samples, summary and/or WAIC |
RW | MCMC Sampling Algorithms |
rwish_chol | The Wishart Distribution |
RW_block | MCMC Sampling Algorithms |
RW_dirichlet | MCMC Sampling Algorithms |
RW_llFunction | MCMC Sampling Algorithms |
RW_llFunction_block | MCMC Sampling Algorithms |
RW_multinomial | MCMC Sampling Algorithms |
RW_PF | MCMC Sampling Algorithms |
RW_PF_block | MCMC Sampling Algorithms |
RW_wishart | MCMC Sampling Algorithms |
sampler | MCMC Sampling Algorithms |
samplerAssignmentRules | Class 'samplerAssignmentRules' |
samplerAssignmentRules-class | Class 'samplerAssignmentRules' |
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_CRP_old | MCMC Sampling Algorithms |
sampler_ess | MCMC Sampling Algorithms |
sampler_posterior_predictive | 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_PF | MCMC Sampling Algorithms |
sampler_RW_PF_block | 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' |
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 |
t | The t Distribution |
testBUGSmodel | Tests BUGS examples in the NIMBLE system |
topologicallySortNodes | Class 'modelBaseClass' |
updateMCMCcomparisonWithHighOrderESS | Re-estimate effective sample size from results of compareMCMCs |
valueInCompiledNimbleFunction | get or set value of member data from a compiled nimbleFunction using a multi-interface |
values | Access or set values for a set of nodes in a model |
values<- | Access or set values for a set of nodes in a model |
which | NIMBLE language functions for R-like vector construction |
Wishart | The Wishart Distribution |
wishart | The Wishart Distribution |
withNimbleOptions | Temporarily set some NIMBLE options. |
-Class | Functions and Classes Internal to NIMBLE |
[,CmodelValues-method,ANY,ANY | Class 'modelValuesBaseClass' |
[,CmodelValues-method,character,missing | Class 'modelValuesBaseClass' |
[-method | Class 'modelValuesBaseClass' |
[-method | Functions and Classes Internal to NIMBLE |
[<--method | Class 'modelValuesBaseClass' |
[<--method | Functions and Classes Internal to NIMBLE |
[[-method | Class 'modelBaseClass' |
[[-method | Class 'modelValuesBaseClass' |
[[-method | Functions and Classes Internal to NIMBLE |
[[<--method | Class 'modelBaseClass' |
[[<--method | Class 'modelValuesBaseClass' |
[[<--method | Functions and Classes Internal to NIMBLE |