Resubmit to CRAN: fix MCMC acronym, add reference, replace dontrun with donttest

Author: gosukehommaEX

CRAN-SUBMISSION

@@ -0,0 +1,3 @@
+Version: 0.1.0
+Date: 2026-04-16 12:04:25 UTC
+SHA: 68be151dc236093159c9cf8849357017fb4a7021

DESCRIPTION

@@ -23,14 +23,17 @@ Description: Provides comprehensive methods to calculate posterior probabilities
     External designs incorporate historical data through power priors
     using exact conjugate representations (Normal-Inverse-Chi-squared for single
     continuous, Normal-Inverse-Wishart for two continuous, and Dirichlet for
-    binary endpoints), enabling closed-form posterior computation without MCMC
-    sampling. This approach significantly reduces computational burden while
-    preserving complete Bayesian rigor. The package also provides grid-search
-    functions to find optimal Go and NoGo thresholds that satisfy user-specified
-    operating characteristic criteria for all supported endpoint types and
-    study designs. S3 print() and plot() methods are provided for all decision
-    probability classes, enabling formatted display and visualisation of
-    Go/NoGo/Gray operating characteristics across treatment scenarios.
+    binary endpoints), enabling closed-form posterior computation without Markov
+    chain Monte Carlo (MCMC) sampling. This approach significantly reduces
+    computational burden while preserving complete Bayesian rigor. The package
+    also provides grid-search functions to find optimal Go and NoGo thresholds
+    that satisfy user-specified operating characteristic criteria for all
+    supported endpoint types and study designs. S3 print() and plot() methods
+    are provided for all decision probability classes, enabling formatted display
+    and visualisation of Go/NoGo/Gray operating characteristics across treatment
+    scenarios.
+    See Kang, Yamaguchi, and Han (2026) <doi:10.1080/10543406.2026.2655410>
+    for the methodological framework.
 License: GPL (>= 2)
 Encoding: UTF-8
 Language: en-US

NEWS.md

@@ -1,5 +1,12 @@
 # BayesianQDM 0.1.0
 
+## Resubmission
+
+* Expanded the MCMC acronym to "Markov chain Monte Carlo (MCMC)" in DESCRIPTION.
+* Added a reference to Kang, Yamaguchi, and Han (2026) in DESCRIPTION.
+* Replaced `\dontrun{}` with `\donttest{}` in examples for `getgamma2bin()` and
+  `getgamma2cont()`.
+
 ## Initial Release
 
 Initial release providing a comprehensive Bayesian quantitative decision-making

R/getgamma2bin.R

@@ -217,7 +217,7 @@
 #' # Example 1: Controlled design, posterior probability
 #' # gamma_go  : smallest gamma_go   s.t. max_{gamma_nogo} Pr(Go)   < 0.05 under Null
 #' # gamma_nogo: smallest gamma_nogo s.t. max_{gamma_go}   Pr(NoGo) < 0.20 under Alt
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'posterior', design = 'controlled',
 #'   GoRegions = 1L, NoGoRegions = 9L,
@@ -244,7 +244,7 @@
 #' }
 #'
 #' # Example 2: Uncontrolled design, posterior probability
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'posterior', design = 'uncontrolled',
 #'   GoRegions = 1L, NoGoRegions = 9L,
@@ -271,7 +271,7 @@
 #' }
 #'
 #' # Example 3: External design, posterior probability
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'posterior', design = 'external',
 #'   GoRegions = 1L, NoGoRegions = 9L,
@@ -298,7 +298,7 @@
 #' }
 #'
 #' # Example 4: Controlled design, predictive probability
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'predictive', design = 'controlled',
 #'   GoRegions = 1L, NoGoRegions = 4L,
@@ -325,7 +325,7 @@
 #' }
 #'
 #' # Example 5: Uncontrolled design, predictive probability
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'predictive', design = 'uncontrolled',
 #'   GoRegions = 1L, NoGoRegions = 4L,
@@ -352,7 +352,7 @@
 #' }
 #'
 #' # Example 6: External design, predictive probability
-#' \dontrun{
+#' \donttest{
 #' getgamma2bin(
 #'   prob = 'predictive', design = 'external',
 #'   GoRegions = 1L, NoGoRegions = 4L,

R/getgamma2cont.R

@@ -238,7 +238,7 @@
 #' # Example 1: Controlled design, posterior probability, vague prior
 #' # gamma_go  : smallest gamma_go   s.t. max_{gamma_nogo} Pr(Go)   < 0.05 under Null
 #' # gamma_nogo: smallest gamma_nogo s.t. max_{gamma_go}   Pr(NoGo) < 0.20 under Alt
-#' \dontrun{
+#' \donttest{
 #' Sigma_null <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Sigma_alt  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' getgamma2cont(
@@ -268,7 +268,7 @@
 #' }
 #'
 #' # Example 2: Uncontrolled design, posterior probability, vague prior
-#' \dontrun{
+#' \donttest{
 #' Sigma_null <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Sigma_alt  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' getgamma2cont(
@@ -298,7 +298,7 @@
 #' }
 #'
 #' # Example 3: External design (control only), posterior probability, NIW prior
-#' \dontrun{
+#' \donttest{
 #' Sigma  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Lambda <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' se_c   <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
@@ -329,7 +329,7 @@
 #' }
 #'
 #' # Example 4: Controlled design, predictive probability, vague prior
-#' \dontrun{
+#' \donttest{
 #' Sigma_null <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Sigma_alt  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' getgamma2cont(
@@ -359,7 +359,7 @@
 #' }
 #'
 #' # Example 5: Uncontrolled design, predictive probability, vague prior
-#' \dontrun{
+#' \donttest{
 #' Sigma_null <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Sigma_alt  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' getgamma2cont(
@@ -389,7 +389,7 @@
 #' }
 #'
 #' # Example 6: External design (control only), predictive probability, NIW prior
-#' \dontrun{
+#' \donttest{
 #' Sigma  <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' Lambda <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)
 #' se_c   <- matrix(c(6400.0, 15.0, 15.0, 36.0), 2, 2)

cran-comments.md

@@ -10,7 +10,12 @@
 
 ## R CMD check results
 
-0 errors | 0 warnings | 0 notes
+0 errors | 0 warnings | 1 note
+
+* checking for future file timestamps ... NOTE
+  unable to verify current time
+  This is a transient network issue in the check environment and is not
+  related to the package itself.
 
 ## Package Summary
 
@@ -39,6 +44,11 @@ operating characteristics across treatment scenarios.
   speed and precision; default values are set conservatively for CRAN checks
 * All examples in the documentation are designed to complete within a few seconds
 
-## Previous CRAN Submissions
+## Resubmission
+
+This is a resubmission following reviewer feedback. The following changes were made:
 
-This is the initial submission to CRAN.
+* Expanded the MCMC acronym to "Markov chain Monte Carlo (MCMC)" in DESCRIPTION.
+* Added a reference to Kang, Yamaguchi, and Han (2026) in DESCRIPTION.
+* Replaced `\dontrun{}` with `\donttest{}` in examples for `getgamma2bin()` and
+  `getgamma2cont()`.