Merge pull request #521 from bbayukari/master

update CRAN version

.gitattributes

@@ -0,0 +1,4 @@
+# All files are checked into the repo with LF
+* text=auto
+# These files are checked out using LF locally
+configure.ac eol=lf

R-package/DESCRIPTION

@@ -32,7 +32,7 @@ Imports:
 LinkingTo: 
  Rcpp,
  RcppEigen
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
 Suggests: 
  testthat,
  knitr,

R-package/NEWS.md

@@ -3,6 +3,10 @@
 * Allow the other criterion for model selection: AUC for (multinomial) logistic regression such as the area under the curve (AUC). 
 * Simplify the C++ code structure. 
 * Fix note "Specified C++11: please update to current default of C++17" in CRAN.
+* Support no-intercept GLM model by param 'fit.intercept'.
+* Allow to restrict the range of estimation for beta by param 'beta.high' and 'beta.low'.
+* Fix a bug when support.size is 0.
+* Add cite message when load 'abess'.
 
 # abess 0.4.6
 

R-package/R/utility.R

@@ -1,7 +1,7 @@
 .onAttach <- 
  function(libname, pkgname) {
  packageStartupMessage("\n Thank you for using abess! To acknowledge our work, please cite the package:")
- packageStartupMessage("\n Zhu J, Wang X, Hu L, Huang J, Jiang K, Zhang Y, Lin S, Zhu J (2022). “abess: A Fast Best Subset Selection Library in Python and R.” Journal of Machine Learning Research, 23(202), 1–7. https://www.jmlr.org/papers/v23/21-1060.html.")
+ packageStartupMessage("\n Zhu J, Wang X, Hu L, Huang J, Jiang K, Zhang Y, Lin S, Zhu J (2022). 'abess: A Fast Best Subset Selection Library in Python and R.' Journal of Machine Learning Research, 23(202), 1-7. https://www.jmlr.org/papers/v23/21-1060.html.")
  }
 
 match_support_size <- function(object, support.size) {