Barış Aşıkgil

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Verified

Barış verified their affiliation via an institutional email.

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• Professor
• Head of Department at Mimar Sinan Fine Arts University

The Bayesian learning provides a natural way to model the nonlinear structure as the artificial neural networks due to their capability to cope with the model complexity. In this paper, an evolutionary Monte Carlo (MC) algorithm is proposed to train the Bayesian neural networks (BNNs) for the time series forecasting. This approach called as Genetic...

A seemingly unrelated regression (SUR) model is defined by a system of linear regression equations in which the disturbances are contemporaneously correlated across equations. However, the disturbances can also be serially correlated in each equation of the system. In these cases, estimating SUR becomes more complicated. Some methods have been cons...

Nonlinear models play an important role in various scientific disciplines and engineering. The parameter estimation of these models should be efficient to make better decisions. Ordinary least squares (OLS) method is used for estimating the parameters of nonlinear regression models when all regression assumptions are satisfied. If there is a proble...

Autoregressive models which include lags of dependent variables are usually used in time series analysis. The correlogram of the series and some information criteria can be used in order to determine the order of these models. The information complexity criterion is considered for autoregressive time series models. A simulation study is performed i...

Studying the observations in regression analysis it is seen that the out-put of regression is affected from outliers in the direction of the depen-dent and / or the independent variables. In this paper multiple outliers are examined in two real data sets. The results concerned with which method can determine multiple outliers better are examined wi...

Bu çalışmanın amacı, Türkiye’de 1960-2014 dönemleri arasında, ekonomik büyüme, elektrik tüketimi ve enflasyon arasındaki ilişkinin kısa ve uzun dönemdeki etkilerinin araştırılmasıdır. Genişletilmiş Dickey-Fuller (ADF) ve Phillips-Perron (PP) birim kök testlerinden faydalanılarak değişkenlerin birinci düzeyde durağan oldukları tespit edilmiştir. Böy...

Petrol kiraları, üretim, ithalat ve tüketim vergileri üzerinden elde edilen gelir olduğu için enerji politikalarının bir parçası olarak değerlendirilir. Türkiye, Hindistan ve Brezilya gibi ülkelerin enerji politikaları, petrol ürünlerine yüksek vergiler uygulanmasından dolayı bu ülkelerin gelir elde etme yöntemlerinin bir parçasıdır. Petrol kiralar...

In recent years, Bitcoin (BTC) has become the most popular digital asset in the cryptocurrency market. Its prices are highly volatile due to rapidly increasing investor interest, making it difficult to predict price movements. The aim of this study is to predict trend reversals in BTC price movements by using tree-based ensemble machine learning te...

Nonlinear models are commonly used for analyzing real-life data such as in medicine, engineering, and economics. To make efficient inferences about model parameter estimations and statistical results in nonlinear regression, assumptions related to error term are needed to be satisfied. Ordinary least squares and some modified least squares methods...

Scalar‐on‐function regression, where the response is scalar‐valued and the predictor consists of random functions, is one of the most important tools for exploring the functional relationship between a scalar response and functional predictor/s. The functional partial least squares method improves estimation accuracy for estimating the regression c...

Ordinary least squares method is usually used for parameter estimation in multiple linear regression models when all regression assumptions are satisfied. One of the problems in multiple linear regression analysis is the presence of serially correlated disturbances. Serial correlation can be formed by autoregressive or moving average models. There...

In this study, a new hybrid forecasting method is proposed. The proposed method is called autoregressive adaptive network fuzzy inference system (AR–ANFIS). AR–ANFIS can be shown in a network structure. The architecture of the network has two parts. The first part is an ANFIS structure and the second part is a linear AR model structure. In the lite...

A few recurrent ANFIS approaches were proposed in the literature. Two main types of recurrences are possible in ANFIS architecture. Feedback can be made for input layer or right sides of Sugeno-type rules. In this study, a new type recurrent ANFIS is proposed for forecasting. Feedback mechanism is embedded to ANFIS by using squares of error terms a...

Nonlinear models are usually encountered in various areas including experimental studies such as physics, chemistry, biology etc. Ordinary least squares is one of the most widely used methods for parameter estimation in different types of nonlinear models. However, there are some regression assumptions need to be satisfied for obtaining efficient p...

In this paper, it is aimed to determine the true regressors explaining the dependent variable in multiple linear regression models and also to find the best model by using two different approaches in the presence of low, medium and high multicollinearity. These approaches compared in this study are genetic algorithm and multivariate adaptive regres...

The purpose of this study is to investigate the relationship between upstream supply chain management practices (strategic supplier partnership, level of information sharing, quality of information sharing) and organizational performance. The fieldwork of the research is conducted in e-tailing sector in Turkey. In this study, self-administered ques...

Regression Error Characteristic (REC) curves can be specified as the modified version of Receiver Operating Characteristic (ROC) curves to regression. ROC curves dealing with classification problems plot false positive ratio on the x-axis versus true positive ratio on the y-axis. However, REC curves dealing with comparison of different regression m...

Objective: The aim of this study is to analyze the pharmaceutical consumption in Turkey and investigate different types of models explaining this consumption by using the panel approach. Material and Methods: Different panel data models were constructed by using the panel data regression in order to explain the relationship between the sales and th...

The education is not only a major sector nowadays, but it is also an investment by parents for their children. Thisstudy aims to investigate the effect of the dimensions (reliability, tangibility, responsiveness, assurance andempathy) of service quality in primary education on parent satisfaction. This research is conducted in a publicprimary schoo...

Newspapers are like goods with a shelf life of one day and they have to be distributed daily basis to the sales points. A problem that most newspaper companies encounter daily is how to predict the right number of newspapers to print and distribute among distinct sales points. The aim is to predict newspaper demand as accurately as possible to meet...

Objective: Nonlinear regression analysis is usually used in medical or biochemical areas in order to estimate unknown parameters. Ordinary least squares method can be considered for parameter estimation. However, efficient parameter estimates can not be obtained with the help of this method when errors are autocorrelated. In this paper, a method ca...

In this study, conducted on 96 employees from production sector in a pharmaceutical company, the effect of transformational leadership behavior on organizational culture is investigated to determine statistically significant relations. The results of the study support the hypotheses. Transformational leadership behavior has a positive and significa...

This study conducted on 100 employees from production sector and 82 employees from service provider sector. The relationship among job satisfaction, organizational commitment and turnover intention are investigated to determine statistically significant relations. The results of the study support the hypotheses. Job Satisfaction has a significant a...

There is an efficiency problem in parameter estimation of nonlinear regression models by using ordinary least squares method when errors are autocorrelated. In order to overcome the problem especially for autore- gressive process some methods have been proposed. Two-stage least squares method has been developed by (3) to obtain more ecient paramete...

There is an efficiency problem in parameter estimation of nonlinear regression models when errors are autocorrelated. In order to overcome the problem especially for autoregressive process some methods have been proposed. In this paper a modified two-stage least squares method has been developed to obtain more efficient parameter estimates than the...

The class of generalized linear models includes models called with respect to the distribution of the dependent variable. These models can be explained by different link functions for Normal, Poisson, Binomial, Gamma and Inverse Gaussian distributions. Because of the possibility of affecting outliers to each other multiple examination is usually pr...

Researchers interested in areas where statistics is used aim to find a model explaining the relationship among variables by means of formulating observations or results of experiments. These models are usually nonlinear models. The relationship among variables in a nonlinear model is given as a nonlinear function of at least one of the parameters....