Yazar "Dunder, Emre" için listeleme
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Energy performance evaluation of OECD countries using Bayesian stochastic frontier analysis and Bayesian network classifiers
Cengiz, Mehmet Ali; Dunder, Emre; Senel, Talat (Taylor & Francis Ltd, 2018)More recently a large amount of interest has been devoted to the use of Bayesian methods for deriving parameter estimates of the stochastic frontier analysis. Bayesian stochastic frontier analysis (BSFA) seems to be a ... -
An Examination of the Correlation Between Science and Technology Attitudes Scale, Frequency of Smartphone Usage Scale and Lifelong Learning Scale Scores Using the Structural Equation Model
Kor, Hakan; Erbay, Hasan; Engin, Melih; Dunder, Emre (Sci Methodical Ctr-Sci Educologica, 2017)Lifelong learning can be defined as all of the activities which aim to develop an individual's skills, knowledge and abilities, socially, individually and professionally. Previous research on lifelong learning has been ... -
A modified information criterion for model selection
Dunder, Emre (Taylor & Francis Inc, 9999)Information criterion is an essential measure in data analysis. Primarily, information criterion is used to choose the statistical models. Because of that role, the development of the criteria becomes very crucial issue. ... -
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 ...
