Начало / Университетът / Факултети / Стопански факултет / Катедри и Академичен състав / Катедри / Статистика и иконометрия / Новини - Катедра Статистика и иконометрия / В International Journal of Computer Science and Information Security бе публикувана статия на докторант Борислава Вригазова

   

17.02.2018

 

В International Journal of Computer Science and Information Security (Vol. 16, No. 1, January 2018) бе публикувана статия на докторант Борислава Вригазова към катедра Статистика и иконометрия:

 

" Nonnegative Garrote as a Variable Selection Method in Panel Data " (pp. 95-106)
Borislava Vrigazova, Sofia University “St. Kliment Ohridski”

 

Abstract
In this research, we broaden the advantages of nonnegative garrote as a feature selection method and empirically show it provides comparable results to panel models. We compare nonnegative garrote to other variable selection methods like ridge, lasso and adaptive lasso and analyze their performance on a dataset, which we have previously analyzed in another research. We conclude by showing that the results from nonnegative garrote are comparable to the robustness checks applied to the panel models to validate statistically significant variables. We conclude that nonnegative garrote is a robust variable selection method for panel orthonormal data as it accounts for the fixed and random effects, which are present in panel datasets.

Keywords: nonnegative garrote, feature selection, panel models, fixed effects