* using log directory 'd:/Rcompile/CRANpkg/local/4.6/GSparO.Rcheck' * using R version 4.6.1 (2026-06-24 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 14.3.0 GNU Fortran (GCC) 14.3.0 * running under: Windows Server 2022 x64 (build 20348) * using session charset: UTF-8 * current time: 2026-08-12 08:05:31 UTC * checking for file 'GSparO/DESCRIPTION' ... OK * this is package 'GSparO' version '1.0' * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking whether package 'GSparO' can be installed ... OK * checking installed package size ... OK * checking package directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... [2s] OK * checking whether the package can be loaded with stated dependencies ... [1s] OK * checking whether the package can be unloaded cleanly ... [1s] OK * checking whether the namespace can be loaded with stated dependencies ... [1s] OK * checking whether the namespace can be unloaded cleanly ... [2s] OK * checking loading without being on the library search path ... [1s] OK * checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... [4s] OK * checking Rd files ... [0s] NOTE checkRd: (-1) GSparO.Rd:23: Lost braces; missing escapes or markup? 23 | Group sparse optimization (GSparO) for least squares regression by using the proximal gradient algorithm to solve the L_{2,1/2} regularization model. | ^ checkRd: (-1) GSparO.Rd:26: Lost braces; missing escapes or markup? 26 | GSparO is group sparse optimization for least squares regression described in [Hu et al(2017)], in which the proximal gradient algorithm is implemented to solve the L_{2,1/2} regularization model. GSparO is an iterative algorithm consisting of a gradient step for the least squares regression and a proximal steps for the L_{2,1/2} penalty, which is analytically formulated in this function. Also, GSparO can solve sparse variable selection problem in absence of group structure. In particular, setting group in GSparO be a vector of ones, GSparO is reduced to the iterative half thresholding algorithm introduced in [Xu et al (2012)]. | ^ checkRd: (-1) GSparO.Rd:26: Lost braces; missing escapes or markup? 26 | GSparO is group sparse optimization for least squares regression described in [Hu et al(2017)], in which the proximal gradient algorithm is implemented to solve the L_{2,1/2} regularization model. GSparO is an iterative algorithm consisting of a gradient step for the least squares regression and a proximal steps for the L_{2,1/2} penalty, which is analytically formulated in this function. Also, GSparO can solve sparse variable selection problem in absence of group structure. In particular, setting group in GSparO be a vector of ones, GSparO is reduced to the iterative half thresholding algorithm introduced in [Xu et al (2012)]. | ^ * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking LazyData ... INFO 'LazyData' is specified without a 'data' directory * checking examples ... [7s] OK * checking PDF version of manual ... [19s] OK * checking HTML version of manual ... [1s] OK * DONE Status: 1 NOTE Check process probably crashed or hung up for 20 minutes ... killed Most likely this happened in the example checks (?), if not, ignore the following last lines of example output: Use c() or as.vector() instead. Warning in (eta/(3 * sqrt(3) * lambda * v + eta)) * Bu[(t + 1):(t + group[j])] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. Warning in (eta/(3 * sqrt(3) * lambda * v + eta)) * Bu[(t + 1):(t + group[j])] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. Warning in (eta/(3 * sqrt(3) * lambda * v + eta)) * Bu[(t + 1):(t + group[j])] : Recycling array of length 1 in array-vector arithmetic is deprecated. Use c() or as.vector() instead. [1] "The error of linear system obtained by this GSparO is 0.000052." [1] "The relative error of selected features this GSparO is 0.001383." > > > > ### *