TY - JOUR
T1 - A comparative study of the lasso-type and heuristic model selection methods
AU - Savin, Ivan
PY - 2013
Y1 - 2013
N2 - This study presents a first comparative analysis of Lasso-type (Lasso, adaptive Lasso, elastic net) and heuristic subset selection methods. Although the Lasso has shown success in many situations, it has some limitations. In particular, inconsistent results are obtained for pairwise highly correlated predictors. An alternative to the Lasso is constituted by model selection based on information criteria (IC), which remain consistent in the situation mentioned. However, these criteria are hard to optimize due to a discrete search space. To overcome this problem, an optimization heuristic (Genetic Algorithm) is applied. To this end, results of aMonte-Carlo simulation study together with an application to an actual empirical problem are reported to illustrate the performance of the methods.
AB - This study presents a first comparative analysis of Lasso-type (Lasso, adaptive Lasso, elastic net) and heuristic subset selection methods. Although the Lasso has shown success in many situations, it has some limitations. In particular, inconsistent results are obtained for pairwise highly correlated predictors. An alternative to the Lasso is constituted by model selection based on information criteria (IC), which remain consistent in the situation mentioned. However, these criteria are hard to optimize due to a discrete search space. To overcome this problem, an optimization heuristic (Genetic Algorithm) is applied. To this end, results of aMonte-Carlo simulation study together with an application to an actual empirical problem are reported to illustrate the performance of the methods.
UR - http://www.scopus.com/inward/record.url?scp=84880552302&partnerID=8YFLogxK
U2 - 10.1515/jbnst-2013-0406
DO - 10.1515/jbnst-2013-0406
M3 - Article
AN - SCOPUS:84880552302
VL - 233
SP - 526
EP - 549
JO - Jahrbucher fur Nationalokonomie und Statistik
JF - Jahrbucher fur Nationalokonomie und Statistik
SN - 0021-4027
IS - 4
ER -