The Experts below are selected from a list of 10650 Experts worldwide ranked by ideXlab platform
Elizbar Nadaraya - One of the best experts on this subject based on the ideXlab platform.
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On Deheuvels' Nonparametric Estimation of Distribution Density
2020Co-Authors: Elizbar Nadaraya, Petre Babilua, I. JavakhishviliAbstract:We establish the limiting Distribution of an integral quadratic deviation of Deheuvels' nonparamet- ric estimation of a multidimensional Distribution Density. © 2007 Bull. Georg. Natl. Acad. Sci.
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On the Wolverton-Wagner Estimate of a Distribution Density
2020Co-Authors: Elizbar Nadaraya, Petre Babilua, I. JavakhishviliAbstract:The result of the work consists mainly in obtaining the limit Distribution of an integral quadratic deviation of the Wolverton-Wagner nonparametric estimate of a multidimensional Distribution Density. © 2007 Bull. Georg. Natl. Acad. Sci.
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On the homogeneity test based on the kernel-type estimators of a Distribution Density
Transactions of A. Razmadze Mathematical Institute, 2018Co-Authors: Petre Babilua, Elizbar NadarayaAbstract:Abstract The test of homogeneity is constructed by using kernel-type estimators of a Distribution Density. The limit power of the constructed test is found for close Pitman-type alternatives. The constructed test is compared with Pearson’s X u -square test.
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On deviations between kernel-type estimators of a Distribution Density in p ⩾ 2 independent samples
Communications in Statistics-theory and Methods, 2017Co-Authors: Petre Babilua, Elizbar NadarayaAbstract:ABSTRACTIn the article, the tests are constructed for the hypotheses that p ⩾ 2 independent samples have the same Distribution Density (homogeneity hypothesis) or have the same well-defined Distribution Density (goodness-of-fit test). The limiting power of the constructed tests is found for some local “close” alternatives.
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On Some Goodness-of-Fit Tests Based on Estimates of Kernel-Type Distribution Densities
Theory of Probability and Its Applications, 2010Co-Authors: Elizbar Nadaraya, Grigol Sokhadze, Petre BabiluaAbstract:A goodness-of-fit test is constructed by using a Wolverton–Wagner Distribution Density estimate. The question as to its consistency is studied. The power asymptotics of the constructed goodness-of-fit test is also studied for certain types of close alternatives.
Hamidreza Bayat - One of the best experts on this subject based on the ideXlab platform.
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Numerical analysis of effect of nanofluid and fin Distribution Density on thermal and hydraulic performance of a heat sink with drop-shaped micropin fins
Journal of Thermal Analysis and Calorimetry, 2019Co-Authors: Farzin Keshavarz, Arash Mirabdolah Lavasani, Hamidreza BayatAbstract:In the present study, the effect of nanofluid and Distribution Density of fin on thermal–hydraulic performance of a heat sink with drop-shaped micropin fins is investigated. Reynolds number is defined based on maximum flow velocity and varies in range of 100 ≤ Re _D ≤ 200 for which, in this range, the flow is laminar and steady. The fins are arranged in two configurations: in-line and staggered. Al_2O_3–water and CuO–water nanofluids with volume fraction of 1% and 4% and Ag_2O–water nanofluid were used to validate the present study. The results showed that using drop-shaped fins instead of circular-shaped fins increases the outlet temperature by 0.6% and decreases the pumping work by 13.3%. Moreover, using Al_2O_3–water nanofluid instead of pure water results in outlet temperature and pump work increases of 0.4% and 1%, respectively. Comparing results of different configurations showed that with low number of fin Density, staggered arrangements provide higher outlet temperature than in-line arrangement. However, for moderate fin Density, in-line arrangements result in higher outlet temperature, and in all fins Distribution Density, staggered arrangements need higher pump work compared to in-line arrangements.
Philippe Du Plessis - One of the best experts on this subject based on the ideXlab platform.
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a novel approach to estimate the Distribution Density and at sea risks of a centrally placed mobile marine vertebrate
Biological Conservation, 2018Co-Authors: Stephen K Pikesley, Pierre Didier Agamboue, Jean Pierre Bayet, Jean Noel Bibang, Eric Augowet Bonguno, Francois Boussamba, Annette C Broderick, Michael S Coyne, Philippe Du PlessisAbstract:Abstract Formulating management strategies for mobile marine species is challenging, as knowledge is required of Distribution, Density, and overlap with putative threats. As a step towards assimilating knowledge, ecological niche models may identify likely suitable habitats for species, but lack the ability to enumerate species densities. Traditionally, this has been catered for by sightings-based distance sampling methods that may have practical and logistical limitations. Here we describe a novel method to estimate at-sea Distribution and densities of a marine vertebrate, using historic aerial surveys of Gabonese leatherback turtle ( Dermochelys coriacea ) nesting beaches and satellite telemetry data of females at sea. We contextualise modelled patterns of Distribution with putative threat layers of boat traffic, including fishing vessels and large ship movements, using Vessel Monitoring System (VMS) and Automatic Identification System (AIS) data. We identify key at-sea areas in which protection for inter-nesting leatherback turtles could be considered within the coastal zone of Gabonese Exclusive Economic Zone (EEZ). Our approach offers a holistic technique that merges multiple datasets and methodologies to build a deeper and insightful knowledge base with which to manage known activities at sea. As such, the methodologies presented in this study could be applied to other species of sea turtles for cumulative assessments; and with adaptation, may have utility in defining critical habitats for other central-place foragers such as pinnipeds, or sea bird species. Although our analysis focuses on a single species, we suggest that putative threats identified within this study (fisheries, seismic activity, general shipping) likely apply to other mobile marine vertebrates of conservation concern within Gabonese and central African coastal waters, such as olive ridley sea turtles ( Lepidochelys olivacea ), humpback dolphins ( Sousa teuszii ) and humpback whales ( Megaptera novaeangliae ).
Archil Gulisashvili - One of the best experts on this subject based on the ideXlab platform.
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Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models
Applied Mathematics and Optimization, 2010Co-Authors: Archil Gulisashvili, Elias M SteinAbstract:We study the asymptotic behavior of Distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the Density of time averages of the squared volatility process and the Density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.
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Two-sided estimates for stock price Distribution densities in jump-diffusion models
arXiv: General Finance, 2010Co-Authors: Archil Gulisashvili, Josep VivesAbstract:We consider uncorrelated Stein-Stein, Heston, and Hull-White models and their perturbations by compound Poisson processes with jump amplitudes distributed according to a double exponential law. Similar perturbations of the Black-Scholes model were studied by S. Kou. For perturbed stochastic volatility models, we obtain two-sided estimates for the stock price Distribution Density and compare the tail behavior of this Density before and after perturbation. It is shown that if the value of the parameter, characterizing the right tail of the double exponential law, is small, then the stock price Density in the perturbed model decays slower than the Density in the original model. On the other hand, if the value of this parameter is large, then there are no significant changes in the behavior of the stock price Distribution Density.
Petre Babilua - One of the best experts on this subject based on the ideXlab platform.
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On Deheuvels' Nonparametric Estimation of Distribution Density
2020Co-Authors: Elizbar Nadaraya, Petre Babilua, I. JavakhishviliAbstract:We establish the limiting Distribution of an integral quadratic deviation of Deheuvels' nonparamet- ric estimation of a multidimensional Distribution Density. © 2007 Bull. Georg. Natl. Acad. Sci.
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On the Wolverton-Wagner Estimate of a Distribution Density
2020Co-Authors: Elizbar Nadaraya, Petre Babilua, I. JavakhishviliAbstract:The result of the work consists mainly in obtaining the limit Distribution of an integral quadratic deviation of the Wolverton-Wagner nonparametric estimate of a multidimensional Distribution Density. © 2007 Bull. Georg. Natl. Acad. Sci.
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On the homogeneity test based on the kernel-type estimators of a Distribution Density
Transactions of A. Razmadze Mathematical Institute, 2018Co-Authors: Petre Babilua, Elizbar NadarayaAbstract:Abstract The test of homogeneity is constructed by using kernel-type estimators of a Distribution Density. The limit power of the constructed test is found for close Pitman-type alternatives. The constructed test is compared with Pearson’s X u -square test.
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On deviations between kernel-type estimators of a Distribution Density in p ⩾ 2 independent samples
Communications in Statistics-theory and Methods, 2017Co-Authors: Petre Babilua, Elizbar NadarayaAbstract:ABSTRACTIn the article, the tests are constructed for the hypotheses that p ⩾ 2 independent samples have the same Distribution Density (homogeneity hypothesis) or have the same well-defined Distribution Density (goodness-of-fit test). The limiting power of the constructed tests is found for some local “close” alternatives.
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On Some Goodness-of-Fit Tests Based on Estimates of Kernel-Type Distribution Densities
Theory of Probability and Its Applications, 2010Co-Authors: Elizbar Nadaraya, Grigol Sokhadze, Petre BabiluaAbstract:A goodness-of-fit test is constructed by using a Wolverton–Wagner Distribution Density estimate. The question as to its consistency is studied. The power asymptotics of the constructed goodness-of-fit test is also studied for certain types of close alternatives.