update date in description and CRAN comments for next devel version

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: BAS
 Version: 1.7.1.9000
-Date: 2023-12-5
+Date: 2023-12-6
 Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
 Authors@R: c(person("Merlise", "Clyde", email="[email protected]",
 	   		       role=c("aut","cre", "cph"),

cran-comments.md

@@ -1,17 +1,7 @@
 # Notes to CRAN
 
-## ReSubmission reason 
+## Submission reason 
 
-Submission prior to Dec 14 required to maintain package on CRAN.
-Status  on CRAN check page  under `Additional Issues` for `valgrind`  showed warnings  `Conditional jump or move depends on uninitialised value(s)`.  
-
-- Initialized vector `se`  via `memset` and `disp = 1.0` in  `fit_glm.c` (issue #72)
-
-- Initialized variables in `hyp1f1.c` from `testthat` (issue #75) 
-
-- Removed models that have zero prior probability in `bas.lm` and `bas.glm` (issue #74)
-
-- Fixed error in `bayesglm.fit` to check arguments `x` or `y` for correct type before calling C  and added unit test (issue #67) 
 
 
 ## Test environments
@@ -30,11 +20,8 @@ Status  on CRAN check page  under `Additional Issues` for `valgrind`  showed war
 ## R CMD check results for this submission
 
 * Mmac, Windows, Ubunto, Debian
- 0 error | 0 warnings | 1 notes
-
-Note: Days since last update: 6
+ 0 error | 0 warnings | 0 notes
 
-(resubmission requested by CRAN)
 
 ## Reverse Dependencies
 

src/hypergeometric1F1.c

@@ -66,8 +66,10 @@ double loghyperg1F1_laplace(double a, double b, double x)
        else mode = mode2;
        //       Rprintf("mode 1 %lf, mode %lf\n", mode1, mode2);
 	if (mode < 0) {
+	  // # nocov start
 	  mode = 0.0;
 	  warning("1F1 Laplace approximation on boundary\n");
+	  // # nocov end
 	}
         else{
 	  /*	  prec = a*mode*(1.0 - mode) + (1.0-mode)*(1.0 - mode)*b +