Description Usage Arguments Details Author(s) Examples
This nimbleFunction generator must be specialized to three required arguments: a model, a modelValues, and a character vector of node names.
1 | decideAndJump(model, mvSaved, calcNodes)
|
model |
An uncompiled or compiled NIMBLE model object. |
mvSaved |
A modelValues object containing identical
variables and logProb variables as the model. Can be
created by |
calcNodes |
A character vector representing a set of nodes in the model (and hence also the modelValues) object. |
Calling decideAndJump(model, mvSaved, calcNodes) will generate a specialized nimbleFunction with four required numeric arguments:
modelLP1: The model log-probability associated with the newly proposed value(s)
modelLP0: The model log-probability associated with the original value(s)
propLP1: The log-probability associated with the proposal forward-transition
propLP0: The log-probability associated with the proposal reverse-tranisiton
Executing this function has the following effects: – Calculate the (log) Metropolis-Hastings ratio, as logMHR = modelLP1 - modelLP0 - propLP1 + propLP0 – Make the proposal acceptance decision based upon the (log) Metropolis-Hastings ratio – If the proposal is accepted, the values and associated logProbs of all calcNodes are copied from the model object into the mvSaved object – If the proposal is rejected, the values and associated logProbs of all calcNodes are copied from the mvSaved object into the model object – Return a logical value, indicating whether the proposal was accepted
Daniel Turek
1 2 | my_decideAndJump <- decideAndJump(Rmodel, mvSaved, calcNodes)
jump <- my_decideAndJump(modelLP1, modelLP0, propLP1, propLP0)
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