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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

Tell me more

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