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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -78,7 +78,7 @@ NIMBLE. Journal of Computational and Graphical Statistics 26:403-413. [https://d

In published work that uses NIMBLE, please also cite the package version:

de Valpine, P., C. Paciorek, D. Turek, N. Michaud, C. Anderson-Bergman, F. Obermeyer, C. Wehrhahn Cortes, A. Rodriguez, D. Temple Lang, W. Zhang, S. Paganin, and P. van Dam-Bates. 2024. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling. doi: 10.5281/zenodo.1211190. R package version 1.4.1, https://cran.r-project.org/package=nimble.
de Valpine, P., C. Paciorek, D. Turek, N. Michaud, C. Anderson-Bergman, F. Obermeyer, C. Wehrhahn Cortes, A. Rodriguez, D. Temple Lang, W. Zhang, S. Paganin, and P. van Dam-Bates. 2024. NIMBLE: MCMC, Particle Filtering, and Programmable Hierarchical Modeling. doi: 10.5281/zenodo.1211190. R package version 1.4.2, https://cran.r-project.org/package=nimble.

To help us track usage to justify funding support for NIMBLE, please include the DOI in the citation.

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4 changes: 2 additions & 2 deletions packages/nimble/DESCRIPTION
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Expand Up @@ -15,8 +15,8 @@ Description: A system for writing hierarchical statistical models largely
of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models,
one can use 'NIMBLE' for writing arbitrary other kinds of model-generic
algorithms as well. A full User Manual is available at <https://r-nimble.org>.
Version: 1.4.2
Date: 2026-04-01
Version: 1.4.3
Date: 2026-05-01
Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>
Authors@R: c(
person("Perry", "de Valpine", role = "aut"),
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2 changes: 1 addition & 1 deletion packages/nimble/R/BUGS_nimbleGraph.R
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Expand Up @@ -194,7 +194,7 @@ getConditionallyIndependentSets <- function(model,

if(!missing(nodes)) {
if(missing(givenNodes))
givenNodesIDs <- setdiff(givenNodeIDs, nodeIDs)
givenNodeIDs <- setdiff(givenNodeIDs, nodeIDs)
}
if(!missing(givenNodes)) {
nodeIDs <- setdiff(nodeIDs, givenNodeIDs)
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6 changes: 3 additions & 3 deletions packages/nimble/R/setupMargNodes.R
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Expand Up @@ -283,7 +283,7 @@ setupMargNodes <- function(model, paramNodes, randomEffectsNodes, calcNodes,
tempDataNodesDefault <- model$getNodeNames(dataOnly = TRUE)
if(paramsHandled)
tempDataNodesDefault <- setdiff(tempDataNodesDefault, paramNodes)
tempDataNodesDefaultParents <- model$getParents(tempDataNodesDefault, upstream = TRUE, stochOnly = TRUE)
tempDataNodesDefaultParents <- model$getParents(tempDataNodesDefault, upstream = TRUE, stochOnly = TRUE, self = TRUE)
# See comment above about why this is necessary:
tempDataNodesDefaultParents <- setdiff(tempDataNodesDefaultParents, tempDataNodesDefault)
reNodesDefault <- intersect(reNodesDefault, tempDataNodesDefaultParents)
Expand All @@ -292,12 +292,12 @@ setupMargNodes <- function(model, paramNodes, randomEffectsNodes, calcNodes,
if(paramsHandled) { # This means reProvided OR paramsProvided. Including parents allows checking
# of potentially missing REs.
reNodesDefault <- intersect(reNodesDefault,
model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE))
model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE, self = TRUE))
} else { # This means !paramsHandled and hence !reProvided AND !paramsProvided
reNodesDefault <- intersect(reNodesDefault,
calcNodes)
reNodesDefault <- intersect(reNodesDefault,
model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE))
model$getParents(calcNodes, upstream=TRUE, stochOnly = TRUE, self = TRUE))
}
}
}
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2 changes: 1 addition & 1 deletion packages/nimble/tests/testthat/test-setupMargNodes.R
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Expand Up @@ -436,7 +436,7 @@ test_that("setupMargNodes finds correct randomEffectsNodes based on calcNodes in
})
m <- nimbleModel(code, data = list(y = c(1, 2)))
SMN <- setupMargNodes(m, calcNodes = c("r", "s"))
expect_identical(SMN$randomEffectsNodes, c("r[1]","r[2]"))
expect_identical(SMN$randomEffectsNodes, c("r[1]","r[2]","s[1]","s[2]"))
expect_identical(SMN$paramNodes, c("p[1]","p[2]"))
})

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