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Recent Submissions

COMPARATIVE STUDY BY ADDING BOOTSTRAPPING STAGE IN CONSTRUCTION OF BIOLOGICAL NETWORKS Kaygusuz, Mehmet Ali; Purutçuoğlu Gazi, Vilda (2025-01-01) Model selection methods are very popular in high-dimensional settings in recent years due to the availability of massive amounts of data, specifically from genetical, image progressing, and financial sources. Therefore, th...
INFERENCE OF TIME SERIES CHAIN GRAPHICAL MODEL Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda (2025-01-01) Biological data can have complex structures due to the high dependence on genes, limited observations, and sparse interactions. This complexity increases when we also consider the influence of time on the construction of t...
Forecasting Drought Phenomena Using a Statistical and Machine Learning-Based Analysis for the Central Anatolia Region, Turkey Turkes, Murat; Özdemir, Ozancan; Yozgatlıgil, Ceylan (2024-12-30) Drought is a major concern in Turkey, significantly affecting agriculture, water resources and the economy, especially in the Central Anatolia region with a semiarid steppe and dry-sub-humid climate. This study aims to dev...
A Comparative Analysis of PISA 2015 Türkiye Studies: Introducing A Variable Selection Model to International Large-Scale Assessments Demirci, Sinem; İlk Dağ, Özlem (2024-12-01) International large-scale assessments have a key role in improving educational, economical, and political systems. By using the data of these assessments, countries can draw conclusions about the status of educational syst...
A Bayesian Approach for Learning Bayesian Network Structures Zareifard, Hamid; Tabar, Vahid Rezaei; Javidian, Mohammad Ali; Yozgatlıgil, Ceylan (2024-12-01) We introduce a Bayesian approach method based on the Gibbs sampler for learning the Bayesian Network structure. For this, the existence and the direction of the edges are specified by a set of parameters. We use the non-in...
Bekenbey AI: Innovative Solutions at the Intersection of Deep Learning and Law Yücesan, Erdicem; Erkan, Mehmet Ali; Deveci, Ali; Medeni, İhsan Tolga (2024-12-01) This research introduces a cutting-edge integration of generative artificial intelligence (AI) within the realm of law, creating a sophisticated application tailored for legal professionals, organizations, and the public. ...
Irregular longitudinal data analysis with statistical and machine learning methods for hazardous asteroids Tanrıverdi, İrem; İlk Dağ, Özlem; Gürkan, Mehmet Atakan (2024-04-01) Observations of the asteroids have been performed as long as it has been feasible by the available observational equipment. Recorded data, going back to 18th century, allowed a classification of these celestial objects’ ha...
PROTECT Başbuğ Erkan, Berna Burçak; EKMEKCİ, PERİHAN ELİF; Murray, Virginia; Crawley, Francis; Zhang, Lili (2024-03-01)
Joint Robust Variable Selection of Mean and Covariance Model via Shrinkage Methods GÜNEY, YEŞİM; Gökalp Yavuz, Fulya; ARSLAN, OLÇAY (2024-01-01) A valuable and robust extension of the traditional joint mean and the covariance models when data subject to outliers and/or heavy-tailed outcomes can be achieved using the joint modelling of location and scatter matrix of...
A Bayesian hybrid method for the analysis of generalized linear models with missing-not-at-random covariates Ciftci, Sezgin; Kalaylıoğlu Akyıldız, Zeynep Işıl (2024-01-01) Missing data handling is one of the main problems in modelling, particularly if the missingness is of type missing-not-at-random (MNAR) where missingness occurs due to the actual value of the observation. The focus of the ...
Optimal model description of finance and human factor indices Kalaycı, Betül; Purutçuoğlu Gazi, Vilda; Weber, Gerhard Wilhelm (2024-01-01) Economists have conducted research on several empirical phenomena regarding the behavior of individual investors, such as how their emotions and opinions influence their decisions. All those emotions and opinions are descr...
Job Flow Patterns and Productivity Dynamics in Turkish Manufacturing Dogan, Ergun; İslam, Muhammed Qamarul; Yazici, Mehmet (2024-01-01) In this paper, we analyze the job creation and destruction process, and the productivity dynamics in Turkish manufacturing by size, export status, import status and ownership by using a comprehensive firm-level dataset for...
The ‘PROTECT’ Essential Elements in Managing Crisis Data Policies Zhang, Lili; Ekmekci, Perihan Elif; Murray, Virginia; Başbuğ Erkan, Berna Burçak; Crawley, Francis P.; Li, Xueting; Li, Yandi (2024-01-01) Based on a literature review, policy study, and a conference session discussion, this paper systematically analyzed seven predominant elements in crisis data policies, namely ‘people, resources, operation, technology, ethi...
Communication and coordination in the 2023 Kahramanmaras earthquakes Comfort, Louise K; ÇELİK, SÜLEYMAN; Başbuğ Erkan, Berna Burçak; Lee, Seunghyun (2024-01-01) The interaction between communication and coordination is central to mobilizing response operations, but the processes vary under critical time constraints, creating disparities in complex operations in practice. To explor...
Learning from stress: Transforming trauma into sustainable risk reduction Başbuğ Erkan, Berna Burçak; ÇELİK, SÜLEYMAN; Comfort, Louise (2023-12-01) This study explores the collective learning process that evolved in the cities, towns, and districts damaged in the February 6, 2023, Kahramanmaraş earthquakes in Türkiye. Employing a multi-methods approach and a dataset c...
Stopping Levels for a spectrally negative Markov Additive process Çağlar, Mine; Vardar Acar, Ceren (2023-12-01) The optimal stopping problem for pricingRussian options in financerequires takingthesupremumof the discounted reward function overall finitestoppingtimes. Weassumethelogarithmof theasset priceisaspectrally negativeMarkov ...
cmaRs: A powerful predictive data mining package in R Yerlikaya-Özkurt, Fatma; Yazıcı, Ceyda; Batmaz, İnci (2023-12-01) Conic Multivariate Adaptive Regression Splines (CMARS) is a very successful method for modeling nonlinear structures in high-dimensional data. It is based on MARS algorithm and utilizes Tikhonov regularization and Conic Qu...
Examining parallelization in kernel regression Oltulu, Orçun; Gökalp Yavuz, Fulya (2023-11-04) For a few decades, parallelization in statistical computing has been an increasing trend, and researchers have put significant effort into converting or adjusting known statistical methods and algorithms in parallel. The m...
Forecasting Performance of Machine Learning, Time Series and Hybrid Methods for Low and High Frequency Time Series Özdemir, Ozancan; Yozgatlıgil, Ceylan (2023-11-01)
A new collective anomaly detection approach using pitch frequency and dissimilarity: Pitchy anomaly detection (PAD) Erkuş, Ekin Can; Purutçuoğlu Gazi, Vilda (2023-09-01) Anomaly detection in time series is an important process that can aid in both preprocessing and postprocessing, particularly in biomedical data modalities where anomalies often signify the presence of disorders that requir...

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