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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 |