version 0.1.1

cran · Jul 2, 2024 · 0f36cc5 · 0f36cc5
1 parent c7c7367
commit 0f36cc5
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Showing 4 changed files with 75 additions and 77 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: LatentBMA
 Type: Package
 Title: Bayesian Model Averaging for Univariate Link Latent Gaussian
         Models
-Version: 0.1.0
+Version: 0.1.1
 Authors@R: c(person("Gregor","Zens",role=c("aut","cre"),email="zens@iiasa.ac.at"),
              person("Mark F.J.","Steel", role="aut"))
 Author: Gregor Zens [aut, cre],
@@ -17,6 +17,6 @@ Imports: ggplot2 (>= 3.5.1), knitr (>= 1.47), mnormt (>= 2.1.1),
 Suggests: rmarkdown
 VignetteBuilder: knitr
 NeedsCompilation: no
-Packaged: 2024-06-26 14:03:10 UTC; Gregor
+Packaged: 2024-07-01 14:06:50 UTC; Gregor
 Repository: CRAN
-Date/Publication: 2024-06-27 14:40:26 UTC
+Date/Publication: 2024-07-01 19:00:08 UTC
diff --git a/MD5 b/MD5
@@ -1,17 +1,17 @@
-3cb18539bc0150660651615d2a4df78d *DESCRIPTION
+3ec1247d0bc639483e2ba37576bba4f5 *DESCRIPTION
 46fba0702ec46659f44900b43c4803cb *LICENSE
 8f09d6d177add4689c76504175a96018 *NAMESPACE
 74591e724f7ecb60de9e78b896197232 *R/gradients.R
 019afda4a5c176b9015825b782e5b6ee *R/likelihoods.R
-3843c9ef189d0e7524baad986f50aba6 *R/mcmc.R
+a033d490b3fc1f7b682894497b815b28 *R/mcmc.R
 d686785c77d9110360b990818ca0e260 *R/priors.R
 2d639ca768bebdb3eaa29b9cf07a7f8f *R/utils.R
 2ff22cd160f0ac7da94bb15f8a968c6d *R/wrapper.R
 aa19cb5b0fbed7d1078fc98a3bc10f4a *build/vignette.rds
 d6be19f04fea7a6d59fa7002398ac548 *inst/CITATION
 171adb67bc108d3a629347767a35b6b2 *inst/doc/LatentBMA_Vignette.R
 38e77a83af3e6ea488c39210fb2f2496 *inst/doc/LatentBMA_Vignette.Rmd
-490b83b90ea82e33ba3395b403d09424 *inst/doc/LatentBMA_Vignette.html
+f5d1e0d4c4002fd96a2e5188c7e7be2f *inst/doc/LatentBMA_Vignette.html
 f03d3abb65e03880982a153a13a58aa2 *man/ULLGM_BMA.Rd
 50f5fcdf1dd43ec71b822194d8142168 *man/plotBeta.Rd
 6c4a0c2066e78db687d20f3a1e5d0355 *man/plotModelSize.Rd

diff --git a/R/mcmc.R b/R/mcmc.R
@@ -109,7 +109,7 @@ ULLGM_BMA_MCMC     = function(X,
   # beta binomial model size prior: P/2 by default
   m           = ifelse(is.null(m), P/2, m)
 
-  # if g prior not fixed, trigger updating of g
+  # if g prior not fixed, trigger updating of g (initialize at g=N)
   if(is.function(gprior)){randomg=TRUE; g = N} else{randomg=FALSE}
 
 
@@ -135,7 +135,6 @@ ULLGM_BMA_MCMC     = function(X,
   theta[c(F, gamma==0)]         = 0
   fit.mean                      = cbind(1, X.curr) %*% beta
 
-
   # for adaptive barker proposal
   tau                           = matrix(0.1, N)
   accept                        = matrix(0, N)
@@ -149,7 +148,6 @@ ULLGM_BMA_MCMC     = function(X,
   sig2.store                    = array(NA, c(nsave, 1))
   g.store                       = array(NA, c(nsave, 1))
 
-
   # some useful precomputations
   ones                          = rep(1, N)
   zeros                         = rep(0, N)
@@ -186,7 +184,7 @@ ULLGM_BMA_MCMC     = function(X,
     # compute gradient of log posterior at proposal value
     Zpmu        = z.prop - fit.mean
     eZp         = exp(z.prop)
-    GradProp    = LogLikGradient(y, z, Ni) - Zmu/sig2
+    GradProp    = LogLikGradient(y, z.prop, Ni) - Zpmu/sig2
 
     # barker proposal correction term
     CorrTerm        = CorrTermBarker(z, z.prop, GradCurr, GradProp, zeros)