# Tagged Questions

LARS stands for Least Angle Regression. It is a feature selection technique for multiple regression that incorporates a penalty.

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### Max steps in lars

I don't know how many steps are necessary for lars() to select the variables till the algorithm proceeds to the saturated fit (especially using the ...
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### Using LASSO from lars (or glmnet) package in R for variable selection

Sorry if this question comes across a little basic. I am looking to use LASSO variable selection for a multiple linear regression model in R. I have 15 predictors, one of which is categorical(will ...
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### LARS - LASSO with weights

I am interested in solving the following problem  \min_{\boldsymbol{\beta}} \left( \mathbf{y}-\mathbf{X}\boldsymbol{\beta} \right)^T W \left( \mathbf{y}-\mathbf{X}\boldsymbol{\beta} \right) + ...
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### Least angle regression packages for R or MATLAB

I am looking for a Least Angle Regression (LAR) packages in R or MATLAB which can be used for classification problems. The only package that I currently know which fits this description is glmpath. ...
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### 'Forward Stagewise' option in LARS algorithm

Can anyone help me understand the forward stagewise part in the LARS algorithm? I was reading the R code and could not figure out what is ...
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### Constant signs of correlation in the active set in least angle regression

I am trying to comprehend the proof of the Least Angle Regression algorithm and I am stuck at certain points. I would appreciate any help that I can get. Let me set the stage: I am following the ...
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### Advantages of doing “double lasso” or performing lasso twice?

I once heard a method of using the lasso twice (like a double-lasso) where you perform lasso on the original set of variables, say S1, obtain a sparse set called S2, and then perform lasso again on ...
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### Rolling window using LARS [closed]

I have written some code for a rolling window in matlab for ridge regression. The code uses a 30 day window to learn the data and outputs a lamda for the least error. I am using financial time series ...
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### LASSO/LARS vs general to specific (GETS) method

I have been wondering, why are LASSO and LARS model selection methods so popular even though they are basically just variations of step-wise forward selection (and thus suffer from path dependency)? ...
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### What problem do shrinkage methods solve?

The holiday season has given me the opportunity to curl up next to the fire with The Elements of Statistical Learning. Coming from a (frequentist) econometrics perspective, I'm having trouble grasping ...
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### Feature selection with k-fold cross-validated least angle regression

I am using the least angle regression (LARS) to extract the most important predictors ($x_1, x_2,...,x_p$) for my response variable ($y$). I have seven predictors ($x_1,x_2,...,x_7$) for each ...