;)
;)
;)
Stata's lasso tools let you extract real features from mountains of data. With those features, you can
Predict outcomes
Characterize groups and patterns in your data
Search over highly nonlinear potential relationships
Perform inference on covariates of interest
Handle endogenous covariates or unobserved confounders
We give you the tools to be sure you are finding real features and not just artifacts in a particular sample.
Why so many uses?
Lasso has its roots in
machine-learning
statistics
econometrics
Which is to say, it has established capabilities in real-world applications, the rigor of known statistical properties, and the promise of yet more applications.
You can use it on smaller datasets too.
Two of the primary uses of lasso are described below:
Learn more about prediction and characterizing patterns
Learn more about inference and endogenous covariates
Learn more about Stata's lasso features.
Read more about lasso in the Lasso Reference Manual. For more examples, see
The Stata Blog: An introduction to the lasso in Stata
The Stata Blog: Using the lasso for inference in high-dimensional models
