Regression modelRegression / GLM

Bayesian LASSO regresija

Bayesian LASSO regresija postavlja dvostruko eksponencijalne (Laplaceove) apriorne raspodjele na regresijske koeficijente, što je Bayesov pandan klasičnoj LASSO kazni. Istovremeno smanjuje male koeficijente prema nuli i provodi meku selekciju varijabli, sve unutar koherentnog okvira posteriorne inferencije koji prirodno kvantificira nesigurnost parametara putem intervala pouzdanosti.

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Izvori

  1. Park, T., & Casella, G. (2008). The Bayesian Lasso. Journal of the American Statistical Association, 103(482), 681–686. DOI: 10.1198/016214508000000337
  2. Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society: Series B, 58(1), 267–288. DOI: 10.1111/j.2517-6161.1996.tb02080.x

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Least Absolute Shrinkage and Selection Operator Regression. ScholarGate. https://scholargate.app/hr/statistics/bayesian-lasso-regression

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ScholarGateBayesian LASSO Regression (Bayesian Least Absolute Shrinkage and Selection Operator Regression). Preuzeto 2026-06-15 s https://scholargate.app/hr/statistics/bayesian-lasso-regression · Skup podataka: https://doi.org/10.5281/zenodo.20539026