Modelling count data via copulas

Safari‐Katesari, Hadi; Samadi, S. Yaser; Zaroudi, Samira

doi:10.1080/02331888.2020.1867140

Cited by 17 publications

(15 citation statements)

References 37 publications

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“…An "intelligent agent" is a system that, by knowing its surroundings, increases its chances of success after analysis [37,38]. Artificial intelligence in the industry today: due to the spread of knowledge and more complex decisionmaking process, the use of information systems, especially artificial intelligence systems in decision making, has become more important [39][40][41][42]. e spread of knowledge in the field of technology and industry and the complexity of environmental decisions-in other words, human life-has attracted the attention of experts for the use of decision support systems in environmental affairs [43,44].…”

Section: Green Supplier Selectionmentioning

confidence: 99%

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Implementation of MCDM-Based Integrated Approach to Identifying the Uncertainty Factors on the Constructional Project

Bagheri

Borouji

Razavian

et al. 2021

Mathematical Problems in Engineering

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Presently, environmental management for companies emphasizing environmental protection has become one of the most critical issues for customers, shareholders, governments, employees, competitors, and global pressures requiring organizations to produce environmentally-friendly products and services. This challenge has created a new concept called green supply chain management in business, which combines environmental thinking with the supply chain. Selection of suppliers by considering risk criteria is a category that has attracted the attention of a large number of researchers in order to select the best suppliers according to uncertain factors. In this research, we aim to select a green supplier considering risk factors using a new MCDM approach under uncertainty. For this selection problem, HF-MAIRCA, a new multicriteria sorting method for many alternatives, has been developed. This is used for sorting the alternatives into predefined, ordered supplier categories. This sorting method can be applied to different environmental problems that have a large number of alternatives. As a result of Iran’s case study, the result shows that materials flexibility and materials quality are essential criteria for green supplier selection.

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Section: Green Supplier Selectionmentioning

confidence: 99%

“…Increasing environmental concerns attract the attention of governments [32][33][34][35], customers, and organizations [36][37][38][39][40][41][42][43][44][45][46].…”

Section: Introductionmentioning

confidence: 99%

Implementation of MCDM-Based Integrated Approach to Identifying the Uncertainty Factors on the Constructional Project

Bagheri

Borouji

Razavian

et al. 2021

Mathematical Problems in Engineering

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show abstract

“…Based on this, we use the following data to show the effectiveness of the proposed method. e employed datasets are Astro-ph [26], Blogs [27], CiteSeer [28], Cora [26], and WebKB [28], and the features that make up the dataset can be expressed as the number of nodes (NN), number of edges (NE), number of communities (NC), modularity (MO), diameter (DA), average degree (AD), average clustering coefficient (ACC), and number of triangles (NT). e criteria used to assess the proposed method, compared to the counterparts, are expressed as follows.…”

Section: Datasets and Evaluation Criteriamentioning

confidence: 99%

“…Social networks play an important role in people's daily lives [27][28][29][30]. Social media creates a substrate for users to share their information, in terms of media, documents, and opinions [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

ECLP: Friend Recommendation Using Ensemble Approach for Detecting Communities Performing Link Prediction

Saeidinezhad

Parvinnia

Boostani

2021

Mathematical Problems in Engineering

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Social networks provide a variety of online services that play an important role in new connections among members to share their favorite media, document, and opinions. For each member, these networks should precisely recommend (predict) the link of members with the highest common interests. Because of the huge volume of users with different types of information, these networks encounter challenges such as dispersion and accuracy of link prediction. Moreover, networks with numerous users have the problem of computational and time complexity. These problems are caused because all the network nodes contribute to calculations of link prediction and friend suggestions. In order to overcome these drawbacks, this paper presents a new link prediction scheme containing three phases to combine local and global network information. In the proposed manner, dense communities with overlap are first detected based on the ensemble node perception method which leads to more relevant nodes and contributes to the link prediction and speeds up the algorithm. Then, these communities are optimized by applying the binary particle swarm optimization method for merging the close clusters. It maximizes the average clustering coefficient (ACC) of the whole network which results in an accurate and precise prediction. In the last phase, relative links are predicted by Adamic/Adar similarity index for each node. The proposed method is applied to Astro-ph, Blogs, CiteSeer, Cora, and WebKB datasets, and its performance is compared to state-of-the-art schemes in terms of several criteria. The results imply that the proposed scheme has a significant accuracy improvement on these datasets.

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“…General constructions of multivariate copulas can be found in [12][13][14][15]. Modern applications of the standard copulas can be found in [16][17][18][19]. When they are made explicit, the above mentioned copulas are often defined with exponential, logarithmic, power, and special integral functions.…”

Section: Introductionmentioning

confidence: 99%

On New Types of Multivariate Trigonometric Copulas

Chesneau

2021

AppliedMath

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Copulas are useful functions for modeling multivariate distributions through their univariate marginal distributions and dependence structures. They have a wide range of applications in all fields of science that deal with multivariate data. While there is a plethora of copulas, those based on trigonometric functions, especially in dimensions greater than two, have received much less attention. They are, however, of interest because of the properties of oscillation and periodicity of the trigonometric functions, which can appear in certain models of correlation of natural phenomena. In order to fill this gap, this paper introduces and investigates two new types of “multivariate trigonometric copulas”. Their main theoretical properties are studied, and some perspectives for applications are sketched for future work. In particular, we show that the proposed copulas are symmetric, not associative, with no orthant dependence, and with copula densities that have wide oscillations, which remains an uncommon property in the field. The expressions of their multivariate Spearman’s rho are also determined. Furthermore, the first type of the proposed copulas has the interesting feature of having a multivariate Spearman’s rho equal to 0 for all of the dimensions. Some graphic evidence supports the findings. Some mathematical formulas involving the product of n trigonometric functions may be of independent interest.

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Modelling count data via copulas

Cited by 17 publications

References 37 publications

Implementation of MCDM-Based Integrated Approach to Identifying the Uncertainty Factors on the Constructional Project

Implementation of MCDM-Based Integrated Approach to Identifying the Uncertainty Factors on the Constructional Project

ECLP: Friend Recommendation Using Ensemble Approach for Detecting Communities Performing Link Prediction

On New Types of Multivariate Trigonometric Copulas

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