# Questions tagged [lars]

LARS stands for Least Angle Regression. It is a penalized estimation and feature selection technique for multiple regression.

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### glmnet vs. lars for computing the lasso

I've seen this post as well as this one regarding the difference between the lars and glmnet solution paths for fitting the ...
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### LARS/GLMNET/Coordinate descent - computational speed vs complexity - a confusing result

The computational complexity of LASSO via LARS is $\mathcal{O}(K^3 + K^2 n)$ see stackexchange post for a $K$ features and $n$ data points. (The derivation in Efron et al., 2004 make sense to me ...
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### R - CV.GLMNET LASSO (binomial) variable reduction - highly correlated variables not zeroing out

I have a dataset of about n = 100,000 observations and p = 247 predictors with one binomial dependent variable (values are 0, 1) I run the following code in R: ...
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### lasso - how to evaluate results

I'm working on lasso as an alternative to step-wise forward/backward regression using the lars package in R. I normalized my variables, calculated the ...
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### explaining LARS algorithm in a simple way [duplicate]

I am thinking to write a LARS algorithm that uses different optimizations in each step. Can somebody briefly explain Least angel regression, LARS (see here) to me? then I will try to write my own LARS ...
1answer
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### How to interprete lasso from lars correctly?

I tried the lars package with R and got the following result. ...
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### how to combine coefficients of a logistic regression model with existing prior knowledge about covariates?

I am working on developing statistical models for fault-localization. on the one hand, i construct a logistic regression model with these considerations: 1-my dependent(response) variable is program ...
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### R - Lasso Regression - different Lambda per regressor

I want to do the following: 1) OLS regression (no penalization term) to get beta coefficients $b_{j}^{*}$; $j$ stands for the variables used to regress. I do this by ...
1answer
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### Why is there no intercept in the lars output for LASSO in Stata?

This is my first time using lars, so this question is probably obvious. When I run lars on my data I get an output with a model and coefficients assigned to predictors, but there is no intercept. I ...
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### Exact definition of Deviance measure in glmnet package, with crossvalidation?

For my current reseach I'm using the Lasso method via the glmnet package in R on a binomial dependent variable. In glmnet the optimal lambda is found via cross-validation and the resulting models ...
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### CV for LASSO tuning parameter using LARS

If I use the LARS algorithm to fit the LASSO path, is it sufficient to cross-validate using the values of $\lambda$ at each step in LARS or is it better to use a finer grid of $\lambda$ values? I ...
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### Parameter tuning in lars (lasso) matlab

I am trying to use lars (matlab implementation:http://www.ece.ubc.ca/~xiaohuic/code/LARS/LARS.htm). I want to do a leave one out cross validation on my data using this code. I have the following ...
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### How to add a non-negative constraint to lasso4j?

Lasso4j is a Java implementation of the Lasso L1-constrained fitting for linear regression. I would like to add a non-negativity constraint on the weights, meaning that the non-zero sparse ...
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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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### 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 ...