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)
&nbsp;

 

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

plot(y,predict(res),pch = 20)
&nbsp;

 

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 4.1.0 (2021-05-18)
# Platform: x86_64-apple-darwin17.0 (64-bit)
# Running under: macOS Big Sur 10.16
# 
# Matrix products: default
# BLAS:   /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.dylib
# LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
# 
# locale:
# [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
# 
# attached base packages:
# [1] stats     graphics  grDevices utils     datasets  methods   base     
# 
# other attached packages:
# [1] susieR_0.11.50
# 
# loaded via a namespace (and not attached):
#  [1] Rcpp_1.0.7        highr_0.9         plyr_1.8.6        compiler_4.1.0   
#  [5] pillar_1.6.2      tools_4.1.0       digest_0.6.27     evaluate_0.14    
#  [9] memoise_2.0.0     lifecycle_1.0.0   tibble_3.1.4      gtable_0.3.0     
# [13] lattice_0.20-44   pkgconfig_2.0.3   rlang_0.4.11      Matrix_1.3-3     
# [17] yaml_2.2.1        pkgdown_1.6.1     xfun_0.24         fastmap_1.1.0    
# [21] dplyr_1.0.7       stringr_1.4.0     knitr_1.33        generics_0.1.0   
# [25] desc_1.3.0        fs_1.5.0          vctrs_0.3.8       systemfonts_1.0.2
# [29] tidyselect_1.1.1  rprojroot_2.0.2   grid_4.1.0        reshape_0.8.8    
# [33] glue_1.4.2        R6_2.5.1          textshaping_0.3.5 fansi_0.5.0      
# [37] rmarkdown_2.9     mixsqp_0.3-46     irlba_2.3.3       purrr_0.3.4      
# [41] ggplot2_3.3.5     magrittr_2.0.1    scales_1.1.1      htmltools_0.5.1.1
# [45] ellipsis_0.3.2    colorspace_2.0-2  ragg_1.1.3        utf8_1.2.2       
# [49] stringi_1.7.3     munsell_0.5.0     cachem_1.0.5      crayon_1.4.1