We propose a new lasso-type estimator of regression coefficients for regression models. Our proposal relies on the recent idea of induced smoothing and leads to estimators with sampling distribution somewhat close to the Normal one, regardless of their true value, along with the corresponding reliable covariance matrix. As a consequence inference (e.g. p-values) may be carried out relatively easily. We present results from some simulation experiments.

The induced smoothed LASSO

GIOVANNA Cilluffo;Stefania La Grutta
2016

Abstract

We propose a new lasso-type estimator of regression coefficients for regression models. Our proposal relies on the recent idea of induced smoothing and leads to estimators with sampling distribution somewhat close to the Normal one, regardless of their true value, along with the corresponding reliable covariance matrix. As a consequence inference (e.g. p-values) may be carried out relatively easily. We present results from some simulation experiments.
2016
Istituto di biomedicina e di immunologia molecolare - IBIM - Sede Palermo
LASSO
induced smoothing
statistical modelling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/374022
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