Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2026Scopus SJRQ2Risk Assessment via Hazard Scenario in Cereal Production Under Rising CO
Susam, Selim Orhun; Peker, Ayse Esra; Hudaverdi, Burcu
Global food security has been seriously threatened by air pollution and climate change. The impact of CO on crop output is complicated because of its interactions with temperature, nutrient availability, and other pollutants, even though it is necessary for photosynthesis. This study develops a copula-based hazard modeling framework to assess how increasing CO concentrations affect cereal production risk across multiple crops. By integrating hazard scenario analysis with localized dependence measures, we estimate both failure probabilities and dynamic associations between CO emissions and cereal yields. A novel localized version of Kendall’s implemented via a Bernstein copula approximation, enables flexible modeling of heterogeneous and nonlinear dependence structures. As the relationship between CO emissions and crop-specific yields changes in both density and direction, it may indicate asymmetries or nonlinearities that are missed by measures of global dependence. Empirical results reveal distinct crop-specific responses. While CO levels enhance yields for rice, millet, and sugar beet, they reduce or destabilize production for rye and lentil, indicating asymmetric sensitivities. Failure probabilities increase with the time horizon, reflecting the accumulation of climate-related production risk. The findings emphasize the significance of integrating probabilistic hazard modeling into climate-resilient agricultural planning and food security policies, as crop-specific risk exposure has increased in recent time periods.
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İncele - MakaleYalnız künye2025Scopus SJRQ2Copula-based conditional reliability with application to rocket motor data
Hudaverdi, Burcu; Susam, Selim Orhun; Chesneau, Christophe
In this paper, we construct conditional reliability in the context of stress-strength models, taking into account the relationship between applied stress and strength. The Bernstein copula approximation is used to calculate the conditional reliability values. Real data from a rocket motor experiment are considered to evaluate the conditional reliability strength of a motor case and the required stress endurance for the motor.
AtıfScopus4WoS5OpenAlex5İncele - MakaleYalnız künye2025Scopus SJRQ4Spearman dependence function-based goodness-of-fit test for the gene's relation
Susam, Selim Orhun; Hudaverdi, Burcu
A gene network represents the relationship between different groups of genes with various functions, aiming to depict how genes collaborate and influence each other’s activities within a biological system. This relationship can be effectively explained using copulas. Therefore, it is crucial to determine which copula best fits the gene data and provide the most accurate explanation of the relationships between gene groups. In this study, our objective is to introduce a Spearman dependence function-based goodness-of-fit test using Bernstein polynomial approximation. We apply this test to identify a copula model that can effectively explain the relationships between gene groups. A Monte Carlo simulation study is conducted to assess the performance of the proposed test. Next, we analyse histone gene groups using data from yeast cell regulation, as provided by Eisen et al. (1998). Specifically, we investigate the dependence model structures of gene interactions for eight histone genes.
AtıfScopus2WoS2OpenAlex2İncele - MakaleYalnız künye2024Scopus SJRQ2Stress–strength reliability for electricity systems based on the Bernstein copula approximation
Susam, Selim Orhun; Hudaverdi, Burcu
Electricity is a critical resource for modern society, and its availability is essential for various aspects of daily life, from powering homes to supporting industrial processes and infrastructure. Ensuring a reliable supply of electricity is vital for economic stability and the well-being of a population. As the world moves toward more sustainable and renewable energy sources, understanding the reliability of these sources compared to traditional fossil fuels is crucial. In this study, we develop a methodology that enables the measurement of stress–strength reliability when electricity consumption is considered as the strength variable, positioned between electricity generation from renewable energy sources and fossil fuels as stress variables. We achieve this using the copula-based reliability with Bernstein copula approximation. The methodology is applied to the U.S. monthly electricity data. The result shows that the current rates of electricity output from fossil fuels and renewables will not be sufficient to meet the demand for electricity.
AtıfScopus2WoS3OpenAlex3İncele - MakaleYalnız künye2023Scopus SJRQ2A weighted independence test based on smooth estimation of Kendall distribution
Susam, Selim Orhun; Hudaverdi, Burcu
In this study, we introduce a nonparametric test of independence which is based on a weighted Cramér-von Mises distance of the Bernstein estimate of the Kendall distribution function. We examine the power and the size of the new weighted test and, we compare it with the non-weighted nonparametric tests of independence through a Monte Carlo simulation study. The simulation results indicate that both of the choices of the weights and the polynomial degree has a significant effect on the test power. Finally, the procedure is applied to a dataset on chemical elements in water samples for the purpose of illustration.
AtıfScopus1WoS1OpenAlex1İncele - MakaleYalnız künye2023Scopus SJRQ3On the weighted tests of independence based on Bernstein empirical copula
Hudaverdi, Burcu; Susam, Selim Orhun
In this article, we propose a flexible weighted test of independence based on Cramér-von Mises statistic of the Bernstein empirical copula process. We investigate the asymptotic properties of the new weighted test. A Monte Carlo study is conducted to measure the power performance of the new test under various dependence structures and also to compare the performance with some other alternative tests. The effects of the weights and the selection of optimal Bernstein polynomial degree are significantly influencing the power of the test according to the particular type of dependence. Finally, the procedure is also applied to a dataset on diabetes for illustrative purpose.
AtıfScopus8WoS8OpenAlex7İncele - MakaleYalnız künye2023Scopus SJRQ3A goodness-of fit improvement based on τ-preserving transformation for semiparametric family of copulas
Susam, Selim Orhun; Hudaverdi, Burcu
In this paper, we study on improving the goodness-of fit for the data by using τ-preserving transform for the semiparametric family of bivariate copulas. We estimate the generator function (Formula presented.) using the Bézier polynomial function and define τ- preserving transformation on the generator function under positive quadrant dependence assumption. We investigate the performance of our methodology on real data example contained life expectancy study. The findings indicate that the model fitting is improved by using τ- preserving transformation.
AtıfScopus3WoS3OpenAlex2İncele - MakaleYalnız künye2023Scopus SJRQ2On the copula-based reliability of stress-strength model under bivariate stress
Hudaverdi, Burcu; Susam, Selim Orhun
In this paper, we consider the stress-strength reliability (Formula presented.) where the strength Y of a component lies between the dependent stress variables (Formula presented.) and (Formula presented.). We propose a copula-based approach for stress-strength reliability having bivariate stress. We obtain R for Farlie-Gumbel-Morgenstern copula with Burr III marginals. Also, we propose a Bernstein copula approximation for evaluating R under the stress-strength setup. We present empirical and maximum likelihood-based estimation procedures and compare their performances by Monte Carlo simulation. We apply the proposed approach to chemical and overt diabetes data for illustration purpose.
AtıfScopus12WoS12OpenAlex11İncele