staged before release

DESCRIPTION

@@ -2,7 +2,7 @@ Package: SANple
 Type: Package
 Title: Fitting Shared Atoms Nested Models via Markov Chains Monte Carlo
 Version: 0.1.1
-Date: 2023-10-09
+Date: 2024-05-13
 Authors@R: c(
     person("Laura", "D'Angelo", ,"laura.dangelo@live.com", 
     role = c("aut", "cre", "cph"),
@@ -27,5 +27,5 @@ Depends:
     scales, RColorBrewer
 LinkingTo: 
     Rcpp, RcppArmadillo, RcppProgress
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Encoding: UTF-8

NEWS.md

@@ -1,12 +1,9 @@
-# SANple (development version)
+# SANple 0.1.1 (development version)
 
--futura versione 0.1.1
-
-* Improve efficiency of stick-breaking computation
-* Improve initialization of the algorithms
-* Changed cpp for loops indexes from int to unsigned int when needed
-* ha senso chiamare gli header di tutti ovunque? credo sia questo che renda il pacchetto pesantissimo
-* Fixed a bug in the full conditional of the concentration parameter for the observational DP of CAM
+* Improved efficiency of stick-breaking computation;
+* Improved initialization of the algorithms, streamlined some scripts;
+* Changed cpp `for loops` indexes from int to unsigned int when needed;
+* Fixed a bug in the full conditional of the concentration parameter for the observational DP of CAM.
 
 # SANple 0.1.0
 

README.md

@@ -1,7 +1,7 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# SANple v0.1.0.9000 <img src="man/figures/sanple_draft.png" align="right" width="120" />
+# SANple v0.1.1 <img src="man/figures/sanple_draft.png" align="right" width="120" />
 
 <!-- badges: start -->
 
@@ -18,7 +18,7 @@ Commit](https://img.shields.io/github/last-commit/laura-dangelo/SANple)](https:/
 The goal of SANple is to estimate Bayesian nested mixture models via
 MCMC methods. Specifically, the package implements the common atoms
 model (Denti et al., 2023), its finite version (D’Angelo et al., 2023),
-and a hybrid finite-infinite model (D’Angelo and Denti, 2023+). All
+and a hybrid finite-infinite model (D’Angelo and Denti, 2024+). All
 models use Gaussian mixtures with a normal-inverse-gamma prior
 distribution on the parameters. Additional functions are provided to
 help analyzing the results of the fitting procedure.
@@ -95,7 +95,7 @@ D’Angelo, L., Canale, A., Yu, Z., Guindani, M. (2023). Bayesian
 nonparametric analysis for the detection of spikes in noisy calcium
 imaging data. *Biometrics* 79(2), 1370–1382.
 
-D’Angelo, L., and Denti, F. (2023+). A finite-infinite shared atoms
+D’Angelo, L., and Denti, F. (2024+). A finite-infinite shared atoms
 nested model for the Bayesian analysis of large grouped data sets.
 *Working paper*, 1–23.
 

cran-comments.md

@@ -1,28 +1,13 @@
-Please note this is a resubmission of this package to CRAN.
+## SANple 0.1.1
 
-Thank you for checking our package. After the inspection, we were notified of the following:
+In this release
 
-* Please do not start the description with "This package", package name, title or similar.
+* we improved efficiency of stick-breaking computation;
+* we improved initialization of the algorithms, and streamlined some scripts;
+* we changed cpp `for loops` indexes from int to unsigned int when needed;
+* we fixed a bug in the full conditional of the concentration parameter for the observational DP of CAM.
 
-The new incipit in the description is: "Estimate Bayesian nested mixture models via Markov Chain Monte Carlo methods.[...]".
 
-* Please add some form of linking to your references.
-
-We added the links for the papers we mentioned.
-
-* Please always explain all acronyms in the description text. -> MCMC
-
-Done.
-
-* Please call the on.exit() functions right after defining 'oldpar' and change the option only afterwards.
-
-We corrected the code as requested.
-
-* Please unwrap the examples if that is feasible and if they can be 
-executed in < 5 sec for each Rd file or create additionally small toy 
-examples to allow automatic testing.
-
-All the old examples have been reduced and are now testable. On our machines, the tests took less than a second to run.
 
 ## R CMD check results
 
@@ -35,30 +20,17 @@ All the old examples have been reduced and are now testable. On our machines, th
 ❯ checking CRAN incoming feasibility ... NOTE
   Maintainer: ‘Laura D'Angelo <laura.dangelo@live.com>’
 
-  New submission
-
-and
-
-Found the following (possibly) invalid DOIs:
+  Found the following (possibly) invalid DOIs:
     DOI: 10.1080/01621459.2021.1933499
       From: DESCRIPTION
       Status: Forbidden
       Message: 403
-    DOI: 10.1111/biom.13626
-      From: DESCRIPTION
-      Status: Forbidden
-      Message: 403
-
+
 However, the links work when building the documentation.
 
 - Running `devtools::check_win_devel()` produces
 
-0 errors | 0 warnings | 1 note
-
-* checking CRAN incoming feasibility ... NOTE
-  Maintainer: 'Laura D'Angelo <laura.dangelo@live.com>'
-
-  New submission
+0 errors | 0 warnings | 0 note
 
 - Finally, in its current state, this package also passes all the standard checks performed via *GitHub actions*.
 

src/funs_cam.cpp

@@ -34,25 +34,6 @@ arma::vec stick_breaking(arma::vec beta_var)
   return(out) ;
 }
 
-/* older version - to be removed
-arma::vec stick_breaking(arma::vec beta_var)
-{
-  int len = beta_var.n_elem ;
-  arma::vec out(len) ;
-  
-  out(0) = beta_var(0) ;
-  for(int k = 1; k < len; k++)
-  {
-    arma::vec tmp(k) ;
-    for(int t = 0; t < k; t++) { tmp(t) = log(1 - beta_var(t)) ; }
-    double tmp1 = arma::accu(tmp) ;
-    if(!arma::is_finite(tmp1)) { tmp1 = log(0) ;}
-    out(k) = exp(log(beta_var(k)) + tmp1) ;
-  }
-  return(out) ;
-}
- */
-
 
 // This function performs steps 1-4 of Algorithm 1 of Denti et al. (2021):
 // - sample observational and distributional slice variables,