Department of Statistics, Conference / Seminar

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Publication (78)

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Purutçuoğlu Gazi, Vilda (27)
Yozgatlıgil, Ceylan (10)
Batmaz, İnci (9)
Akkaya, Ayşen (5)
İlk Dağ, Özlem (4)

Stochastic simulation (3)
Time series (3)
Biochemical systems (2)
Biological networks (2)
Drought (2)

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1997 - 1999 (1)
2000 - 2009 (9)
2010 - 2020 (68)

Recent Submissions

Estimation of AR(1) Model Having Generalized Logistic Disturbances
Akkaya, Ayşen; Türker Bayrak, Özlem (null; 2020-01-02)
Non-normality is becoming a common feature in real life applications. Using non-normal disturbances in autoregressive models induces non-linearity in the likelihood equations so that maximum likelihood estimators cannot be...
StreamMARS: A Streaming Multivariate Adaptive Regression Splines Algorithm
Computers and internet have become inevitable parts of our life in the 1990s, and afterwards, bulk of data are started being recorded in digital platforms automatically. To extract meaningful patterns from such data comput...
Hands-on Introduction Course in R
GÖKALP YAVUZ, FULYA (null; 2019-11-28)
There is a common sense on the importance of Big Data and Data Science topics in both ‘Academia’ and ‘Industry’. R is one of the interactive application tools which handles the data manipulation, statistical analyses and v...
Bootstrap-based Model Selection Criteria in Biological Networks
Kaygusuz, Mehmet Ali; Purutçuoğlu Gazi, Vilda (null; 2019-10-26)
Seven European colorectal cancer predisposing SNPs are associated with CRC and its prognosis in Turkish population
Cumaogullari, O.; Charyyeva, S.; Abaci, E.; Bilici, Z.; Ozakinci, H.; Ilk, O.; Kuzu, A.; Ozdag, H. (2019-10-01)
Adaptive estimation of autoregressive models under long-tailed symmetric distribution
Yentür, Begüm; Bayrak, Özlem Türker; Akkaya, Ayşen (2019-07-08)
In this paper, we consider the autoregressive models where the error term is non-normal; specifically belongs to a long-tailed symmetric distribution family since it is more relevant in practice than the normal distributio...
Calculation of optimal number of Monte Carlo runs for normally distributed datasets
Erkuş, Ekin Can; Purutçuoğlu Gazi, Vilda (null; 2019-03-10)
Examining the maps of air transport network characteristics
Kılıç Depren, Serpil; Gökalp Yavuz, Fulya (2018-11-05)
Understanding the role of air transportation structure increases the economic and social assets in local and global scale. Identifying that role is required for an effective air transportation management, as well. Differen...
Understanding Drought with Copula Functions: Case Study for Konya Province
Evkaya, Ömer Ozan; Yozgatlıgil, Ceylan; Selçuk Kestel, Ayşe Sevtap (null; 2018-10-07)
Drought is one of the most drastic and complex natural phenomenon in the world, a major reason for undesired agricultural, economic and environmental damages. For this reason, the objective identification of drought and it...
Model selection in the construction of biological networks under the steady-state conditions
Bülbül, Gül Bahar; Purutçuoğlu Gazi, Vilda (null; 2018-10-04)
The model selection is a decision problem to choose which variables should be included in a statistical model among all plausible models that could be constructed. There are many applications of this problem in different f...
Estimation of gynecological cancer networks via target proteins and risk factors
Bahçıvancı, Başak; Purutçuoğlu Gazi, Vilda; Purutçuoğlu, Eda (2018-09-22)
Abstract—The construction of biological networks has certain challenges due to its high dimension, sparse structure and very limited number of observations. Thus, specific modeling approaches have been suggested to deal wi...
Semi-Bayesian Inference of Time Series Chain Graphical Models in Biological Networks
Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda (null; 2018-09-20)
The construction of biological networks via time-course datasets can be performed both deterministic models such as ordinary differential equations and stochastic models such as diffusion approximation. Between these two b...
Detection of Binding Sites of Chip-seq Data via Hidden Markov Model and Frequentist Inference of Model Parameters
Doğan Dar, Elif; Purutçuoğlu Gazi, Vilda (2018-06-27)
The hidden Markov model (HMM) is one of the major modeling approaches that is based on the graphical representation inthe form of a chain. In this structure, we have a sequence of multinomial “state...
Modeling of Breast and Gynecological Cancers Data and Investigating New Biological Findings
Ağyüz, Umut; Purutçuoğlu Gazi, Vilda (null; 2018-06-27)
The breast and gynecological cancers are two most common fatal cancers’ types in women in the world [1]. In oncological literature, these two cancers types are typically worked together since they are the risk factors of e...
Maximum Loss of Spectrally Negative Lévy Processes
VARDAR ACAR, CEREN; ÇAĞLAR, MİNE (null; 2018-06-21)
The joint distribution of the maximum loss and the maximum gain is obtained for a spectrally negative L,vy process until the passage time of a given level. Their marginal distributions up to an independent exponential time...
Coşkun, Buket; Vardar Acar, Ceren (null; 2018-04-30)
In this study, we mainly propose an algorithm to generate correlated random walk converging to fractional Brownian motion, with Hurst parameter, H∈ [1/2,1]. The increments of this random walk are simulated from Bernoulli d...
Input variable selection for hydrological predictions in ungauged catchments: with or without clustering
Doğulu, Nilay; Batmaz, İnci; Kentel Erdoğan, Elçin (null; 2018-04-08)
A key step in data-driven environmental modelling, including for hydrological purposes, is input variable selection (IVS) to ensure that the least number of variables with minimum redundancy are used to characterize the in...
Clustering approaches for analysing similarity in ungagued catchments: input variable selection for hydrological predictions
Doğulu, Nilay; Batmaz, İnci; Kentel Erdoğan, Elçin (2018-04-08)
Catchments are hydrological units that exhibit unique but distinct features that greatly contribute to heterogeneity and complexity of rainfall-runoff processes. While the lure of understanding such diversity has underpinn...
A Comparative Study on Learning to Rank with Computational Methods
Batmaz, İnci; Karagöz, Pınar; Serdar, Gulsah (2017-12-14)
Learning to rank is a supervised learning problem that aims to construct a ranking model. The most common application of learning to rank is to rank a set of documents against a query. In this work, we focus on pointwise a...
Maximum Loss and Maximum Gain of Spectrally Negative Levy Processes
Vardar Acar, Ceren; ÇAĞLAR, MİNE (2017-12-08)
The joint distribution of the maximum loss and the maximum gain is obtained for a spectrally negative L´evy process until the passage time of a given level. Their marginal distributions up to an independent exponential tim...
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