R: Basic nimbleFunctions for using a NIMBLE model with sets of...

simNodesMV {nimble} | R Documentation

## Basic nimbleFunctions for using a NIMBLE model with sets of stored values

### Description

simulate, calculate, or get the existing log probabilities for values in a modelValues object using a NIMBLE model

### Usage

    simNodesMV(model, mv, nodes)

    calcNodesMV(model, mv, nodes)

    getLogProbNodesMV(model, mv, nodes)

### Arguments

`model` | A nimble model.
`mv` | A modelValues object in which multiple sets of model variables and their corresponding logProb values are or will be saved. `mv` must include the nodes provided
`nodes` | A set of nodes. If none are provided, default is all `model$getNodeNames()`

### Details

`simNodesMV` simulates values in the given nodes and saves them in `mv`. `calcNodesMV` calculates these nodes for each row of `mv` and returns a vector of the total log probabilities (densities) for each row. `getLogProbNodesMV` is like `calcNodesMV` without actually doing the calculations.

Each of these will expand variables or index blocks and topologically sort them so that each node's parent nodes are processed before itself.

`getLogProbMV` should be used carefully. It is generally for situations where the logProb values are guaranteed to have already been calculated, and all that is needed is to query them. The risk is that a program may have changed the values in the nodes, in which case `getLogProbMV` would collect logProb values that are out of date with the node values.

### Value

from `simNodesMV`: NULL. from `calcNodesMV` and `getLogProbMV`: a vector of the sum of log probabilities (densities) from any stochastic nodes in `nodes`.

### Run time arguments

- `m`

  (`simNodesMV` only). Number of simulations requested.

- `saveLP`

  (`calcNodesMV`only). Whether to save the logProb values in `mv`. Should be given as `TRUE` unless there is a good reason not to.

### Author(s)

Clifford Anderson-Bergman

### Examples

    code <- nimbleCode({
    for(i in 1:5)
    x[i] ~ dnorm(0,1)
    })

    myModel <- nimbleModel(code)
    myMV <- modelValues(myModel)

    Rsim <- simNodesMV(myModel, myMV)
    Rcalc <- calcNodesMV(myModel, myMV)
    Rglp <- getLogProbNodesMV(myModel, myMV)
    ## Not run:
      cModel <- compileNimble(myModel)
      Csim <- compileNimble(Rsim, project = myModel)
      Ccalc <- compileNimble(Rcalc, project = myModel)
      Cglp <- compileNimble(Rglp, project = myModel)
      Csim$run(10)
      Ccalc$run(saveLP = TRUE)
      Cglp$run()	#Gives identical answers to Ccalc because logProbs were saved
      Csim$run(10)
      Ccalc$run(saveLP = FALSE)
      Cglp$run()	  #Gives wrong answers because logProbs were not saved

    ## End(Not run)

[Package nimble version 0.9.1 Index]