PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY

In this paper we will estimate the parameters of the cumulative distribution functions for marginals for bi-variates and, at the same time, those of the copula that connects them, using a sample of a uniform random variable that depends on these parameters. We will also use the \chi_{1;0.99}^2=9.63...

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Main Authors: Daniel Ciuiu, Romică Trandafir, Radu Drobot
Format: Article
Language:English
Published: Conspress 2014-03-01
Series:Romanian Journal of Mathematics and Computer Science
Subjects:
Online Access:http://www.rjm-cs.ro/CiuiuTrandafirDrobot1-2014.pdf
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spelling doaj-78770e4560aa4aa5a3f5723892c94e692020-11-24T22:15:15ZengConspressRomanian Journal of Mathematics and Computer Science2247-689X2014-03-01412743PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGYDaniel Ciuiu0Romică Trandafir1Radu Drobot2Department of Mathematics and Computer Science, Technical University of Civil Engineering of Bucharest, Romania, and Romanian Institute for Economic Forecasting Bucharest, Romania, E-mail: dciuiu@yahoo.comDepartment of Mathematics and Computer Science, Technical University of Civil Engineering of Bucharest, Romania, E-mail: romica@utcb.roDepartment of Hydrotechnic Engineering, Technical University of Civil Engineering of Bucharest, Romania, E-mail: drobot@utcb.roIn this paper we will estimate the parameters of the cumulative distribution functions for marginals for bi-variates and, at the same time, those of the copula that connects them, using a sample of a uniform random variable that depends on these parameters. We will also use the \chi_{1;0.99}^2=9.6349 test for the validation of the model. In fact, the proposed method is a generalization of the PWM (Probability Weighted Moments) method used in literature. For the PWM method there are also used some moments of a uniform random variable, but only for a marginal. In our method we use the uniform random variable for both the marginal and the copula. As an application, we will consider the maximum discharges and the volumes of the floods on the Danube River, connected by a copula in a given gauge station. In this case study, we will estimate the parameters for both the marginal distributions and the copula using the method presented in this paper.http://www.rjm-cs.ro/CiuiuTrandafirDrobot1-2014.pdfArchimedean copulamethod of the uniform random variable momentsisolines of exceeding probabilitiesmodel's validationbi-variatesmaximum discharge and volume of the floods
collection DOAJ
language English
format Article
sources DOAJ
author Daniel Ciuiu
Romică Trandafir
Radu Drobot
spellingShingle Daniel Ciuiu
Romică Trandafir
Radu Drobot
PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
Romanian Journal of Mathematics and Computer Science
Archimedean copula
method of the uniform random variable moments
isolines of exceeding probabilities
model's validation
bi-variates
maximum discharge and volume of the floods
author_facet Daniel Ciuiu
Romică Trandafir
Radu Drobot
author_sort Daniel Ciuiu
title PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
title_short PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
title_full PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
title_fullStr PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
title_full_unstemmed PARAMETER ESTIMATION OF THE MARGINAL CUMULATIVE DISTRIBUTION FUNCTIONS AND OF THE COPULA APPLIED IN HYDROLOGY
title_sort parameter estimation of the marginal cumulative distribution functions and of the copula applied in hydrology
publisher Conspress
series Romanian Journal of Mathematics and Computer Science
issn 2247-689X
publishDate 2014-03-01
description In this paper we will estimate the parameters of the cumulative distribution functions for marginals for bi-variates and, at the same time, those of the copula that connects them, using a sample of a uniform random variable that depends on these parameters. We will also use the \chi_{1;0.99}^2=9.6349 test for the validation of the model. In fact, the proposed method is a generalization of the PWM (Probability Weighted Moments) method used in literature. For the PWM method there are also used some moments of a uniform random variable, but only for a marginal. In our method we use the uniform random variable for both the marginal and the copula. As an application, we will consider the maximum discharges and the volumes of the floods on the Danube River, connected by a copula in a given gauge station. In this case study, we will estimate the parameters for both the marginal distributions and the copula using the method presented in this paper.
topic Archimedean copula
method of the uniform random variable moments
isolines of exceeding probabilities
model's validation
bi-variates
maximum discharge and volume of the floods
url http://www.rjm-cs.ro/CiuiuTrandafirDrobot1-2014.pdf
work_keys_str_mv AT danielciuiu parameterestimationofthemarginalcumulativedistributionfunctionsandofthecopulaappliedinhydrology
AT romicatrandafir parameterestimationofthemarginalcumulativedistributionfunctionsandofthecopulaappliedinhydrology
AT radudrobot parameterestimationofthemarginalcumulativedistributionfunctionsandofthecopulaappliedinhydrology
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