Results 11 to 20 of about 2,844,453 (243)

Copulas for statistical signal processing (Part I) : extensions and generalization [PDF]

open access: yes, 2014
Existing works on multivariate distributions mainly focus on limited distribution functions and require that the associated marginal distributions belong to the same family. Although this simplifies problems, it may fail to deal with practical cases when
Wang, Zheng   +4 more
core   +3 more sources

Approximation multivariate distribution of main indices of tehran stock exchange with pair-copula [PDF]

open access: yes, 2013
The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula.
Parham, Gholamali   +2 more
core   +4 more sources

Copula Functions for Spatial Survival Data Analysis [PDF]

open access: yesJournal of Sciences, Islamic Republic of Iran, 2023
Many survival data analyses aim to assess the effect of different risk factors on survival time‎. ‎In some studies‎, ‎the survival times are correlated‎, ‎and the dependence between survival times is related to their spatial locations‎.
Mohsen Mohammadzadeh   +2 more
doaj   +1 more source

Application of Copula functions in hydrology and water resources: a state-of-the-art review

open access: yesShui kexue jinzhan, 2021
Copula functions, which are flexible tools for the derivation of joint probability distributions, have been widely and effectively used to deal with multivariable analysis problems in the field of hydrology and water resources.
Zhangjun LIU   +4 more
doaj   +1 more source

Conditional independence and predictive copula

open access: yes4 open, 2022
In this paper, we address the concept of conditional independence between two random variables X and Y given the entity Θ. We identify the impact of conditional independence on the analytic form of the predictive 2-copula between X and Y.
González-López V.A.   +1 more
doaj   +1 more source

Correlation between Rainfall and Runoff in Fuchun River Basin Based on Copula Functions and Kernel Density Estimation [PDF]

open access: yes长江科学院院报
[Objective] Rainfall and runoff are two important hydrological variables in river basins, exhibiting the characteristic of random distribution. In-depth analysis of the relationship between rainfall and runoff holds significant importance for watershed ...
YANG Sheng-mei, ZHU De-kang, CHENG Xiang, LI Bo, ZHU Yan-ze, MA Wen-sheng
doaj   +1 more source

Pairs Trading; A Comparison between Student-t and Vine Copulas [PDF]

open access: yesتحقیقات مالی, 2022
Objective: The main purpose of the present research was to compare the performance of pairs trading based on the Vine Copula, Student's t Copula, and Distance approaches. This was done for the first time on the Tehran Stock Exchange (TSE).
Maryam Davallou, Ardavan Yazdi
doaj   +1 more source

A copula-based bivariate integer-valued autoregressive process with application

open access: yesModern Stochastics: Theory and Applications, 2019
A bivariate integer-valued autoregressive process of order 1 (BINAR(1)) with copula-joint innovations is studied. Different parameter estimation methods are analyzed and compared via Monte Carlo simulations with emphasis on estimation of the copula ...
Andrius Buteikis, Remigijus Leipus
doaj   +1 more source

Analyzing the duration frequency and severity of drought using copula function in the Yazd city

open access: yesJournal of Water and Climate Change, 2022
Duration and severity are the two main variables used in drought analysis. The copula functions are appropriate for multivariate drought analysis, as it lacks the limitations of the classical multivariate distribution function.
Mehrtash EskandariPour   +1 more
doaj   +1 more source

Bayesian Nonparametric Inference for a Multivariate Copula Function [PDF]

open access: yes, 2014
The paper presents a general Bayesian nonparametric approach for estimating a high dimensional copula. We first introduce the skew-normal copula, which we then extend to an infinite mixture model.
Wu, Juan, Wang, Xue, Walker, Stephen G.
core   +1 more source

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