lasso2
L1 constrained estimation aka 'lasso' for R
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
UnverifiedOverview
What is lasso2?
The lasso2 package provides functions for L1 constrained estimation or the lasso method in R, enabling efficient variable selection and regularization.
Key differentiator
“The lasso2 package stands out as an essential tool in the R ecosystem for performing L1 constrained estimation, offering efficient and robust methods for variable selection and regularization.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
lasso2 has not been updated in several years and does not leverage newer R functionalities or improvements.
The package lacks comprehensive documentation, making it difficult for new users to understand how to use the functions effectively without deep statistical knowledge.
lasso2 may struggle with computational efficiency when handling extremely large datasets due to its age and lack of optimization for modern computing environments.
Fit analysis
Who is it for?
✓ Best for
Researchers needing efficient variable selection and regularization techniques for high-dimensional datasets
Academics working on statistical modeling with R who require L1 constrained estimation methods
✕ Not a fit for
Developers looking for a full-stack framework or platform
Projects requiring real-time data processing capabilities
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with lasso2
Step-by-step setup guide with code examples and common gotchas.