A minimal example

In this short vignette, we fit a sparse linear regression model with up to L > 0 non-zero effects. Generally, there is no harm in over-stating L (that is, the method is pretty robust to overfitting), except that computation will grow as L grows.

Here is a minimal example:

library(susieR)
set.seed(1)
n    <- 1000
p    <- 1000
beta <- rep(0,p)
beta[c(1,2,300,400)] <- 1
X   <- matrix(rnorm(n*p),nrow=n,ncol=p)
y   <- X %*% beta + rnorm(n)
res <- susie(X,y,L=10)
plot(coef(res)[-1],pch = 20)

Plot the ground-truth outcomes vs. the predicted outcomes:

plot(y,predict(res),pch = 20)

Session information

Here are some details about the computing environment, including the versions of R, and the R packages, used to generate these results.

sessionInfo()
# R version 4.4.3 (2025-02-28)
# Platform: x86_64-conda-linux-gnu
# Running under: Linux Mint 22
# 
# Matrix products: default
# BLAS/LAPACK: /home/gw/.pixi/envs/r-base/lib/libopenblasp-r0.3.30.so;  LAPACK version 3.12.0
# 
# locale:
#  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
# [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
# 
# time zone: America/New_York
# tzcode source: system (glibc)
# 
# attached base packages:
# [1] stats     graphics  grDevices utils     datasets  methods   base     
# 
# other attached packages:
# [1] susieR_0.14.21
# 
# loaded via a namespace (and not attached):
#  [1] Matrix_1.7-4       gtable_0.3.6       jsonlite_2.0.0     dplyr_1.1.4       
#  [5] compiler_4.4.3     crayon_1.5.3       Rcpp_1.1.0         tidyselect_1.2.1  
#  [9] parallel_4.4.3     jquerylib_0.1.4    systemfonts_1.2.3  scales_1.4.0      
# [13] textshaping_1.0.3  yaml_2.3.10        fastmap_1.2.0      lattice_0.22-7    
# [17] plyr_1.8.9         ggplot2_4.0.0      R6_2.6.1           generics_0.1.4    
# [21] mixsqp_0.3-54      knitr_1.50         htmlwidgets_1.6.4  tibble_3.3.0      
# [25] desc_1.4.3         RcppZiggurat_0.1.8 bslib_0.9.0        pillar_1.11.1     
# [29] RColorBrewer_1.1-3 rlang_1.1.6        reshape_0.8.10     cachem_1.1.0      
# [33] xfun_0.53          fs_1.6.6           sass_0.4.10        S7_0.2.0          
# [37] RcppParallel_5.1.9 cli_3.6.5          pkgdown_2.1.3      magrittr_2.0.4    
# [41] digest_0.6.37      grid_4.4.3         irlba_2.3.5.1      lifecycle_1.0.4   
# [45] vctrs_0.6.5        Rfast_2.1.0        evaluate_1.0.5     glue_1.8.0        
# [49] farver_2.1.2       ragg_1.5.0         rmarkdown_2.29     matrixStats_1.5.0 
# [53] tools_4.4.3        pkgconfig_2.0.3    htmltools_0.5.8.1

Matthew Stephens

2025-09-24

Session information