eyedata

Gene expression data (200 genes, 120 samples) from microarray experiments on mammalian eye tissue reported by Scheetz et al. (2006).

Fast tools for fitting sparse generalized linear models with convex
penalties (lasso) and concave penalties (smoothly clipped absolute
deviation and minimax concave penalty). Computation uses multi-stage convex
relaxation and pathwise coordinate optimization with warm starts,
active-set updates, and screening rules. Core solvers are implemented in
C++, and coefficient paths are stored as sparse matrices for memory
efficiency.

Tuo Zhao

picasso

Sparse Learning with Convex and Concave Penalties

Jason Ge

Xingguo Li

Haoming Jiang

Mengdi Wang

Tong Zhang

Han Liu

Gael Guennebaud

Benoit Jacob

Eigen Library Authors

eyedata function

A list with components:<dl>
 <dt>x</dt>
<dd>A 120 by 200 matrix of gene probes.</dd> <dt>y</dt>
<dd>A numeric response vector of length 120 representing the expression level of the TRIM32 gene.</dd> 
</dl>

Format

Xingguo Li, Tuo Zhao, Tong Zhang and Han Liu 
Maintainer: Tuo Zhao &lt;tourzhao@gatech.edu&gt;

Author

Bardet-Biedl Syndrome Gene Expression Data from Scheetz et al. (2006) — eyedata

A list with components:<dl>
 <dt>x</dt>
<dd>A 120 by 200 matrix of gene probes.</dd>

 <dt>y</dt>
<dd>A numeric response vector of length 120 representing the expression level of the TRIM32 gene.</dd>

 
</dl>

Xingguo Li, Tuo Zhao, Tong Zhang and Han Liu 
Maintainer: Tuo Zhao &lt;tourzhao@gatech.edu&gt;

eyedata: Bardet-Biedl Syndrome Gene Expression Data from Scheetz et al. (2006)

Description

Usage

Arguments

Format

Author

Details

References

See Also

Examples