Yazar "Gumustekin, Serpil" için listeleme
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Particle swarm optimization-based variable selection in Poisson regression analysis via information complexity-type criteria
Koc, Haydar; Dunder, Emre; Gumustekin, Serpil; Koc, Tuba; Cengiz, Mehmet Ali (Taylor & Francis Inc, 2018)Modeling of count responses is widely performed via Poisson regression models. This paper covers the problem of variable selection in Poisson regression analysis. The basic emphasis of this paper is to present the usefulness ... -
Subset selection in quantile regression analysis via alternative Bayesian information criteria and heuristic optimization
Dunder, Emre; Gumustekin, Serpil; Murat, Naci; Cengiz, Mehmet Ali (Taylor & Francis Inc, 2017)Subset selection is an extensively studied problem in statistical learning. Especially it becomes popular for regression analysis. This problem has considerable attention for generalized linear models as well as other types ... -
Variable selection in gamma regression models via artificial bee colony algorithm
Dunder, Emre; Gumustekin, Serpil; Cengiz, Mehmet Ali (Taylor & Francis Ltd, 2018)Variable selection is an important task in regression analysis. Performance of the statistical model highly depends on the determination of the subset of predictors. There are several methods to select most relevant variables ... -
Variable selection in linear regression analysis with alternative Bayesian information criteria using differential evaluation algorithm
Dunder, Emre; Gumustekin, Serpil; Murat, Naci; Cengiz, Mehmet Ali (Taylor & Francis Inc, 2018)In statistical analysis, one of the most important subjects is to select relevant exploratory variables that perfectly explain the dependent variable. Variable selection methods are usually performed within regression ...
