scholarly journals A Study on Modelling of Bivariate Competing Risks with Archimedean Copulas

2021 ◽  
pp. 14-21
Author(s):  
Cigdem Topcu Guloksuz
Keyword(s):  
Competing Risks ◽  
Distribution Functions ◽  
Archimedean Copula ◽  
Archimedean Copulas ◽  
Copula Functions ◽  
Failure Times ◽  
Specific Distribution ◽  
Independent Censoring ◽  
Set Up ◽  
Best Fit

In this study we consider Archimedean copula functions to obtain estimates of cause-specific distribution functions in bivariate competing risks set up. We assume that two failure times of the same group are dependent and this dependency can be modeled by an Archimedean copula. Based on the Archimedean copula which gives best fit to the competing risk data with independent censoring we obtain the estimates of cause specific sub distributions.

Archimedean copulas, exchangeability, and max-stability

1994 ◽  
Vol 31 (2) ◽  
pp. 383-390 ◽  
Author(s):  
Rocco Ballerini
Keyword(s):  
Random Variables ◽  
Distribution Functions ◽  
Archimedean Copula ◽  
Archimedean Copulas ◽  
Monotone Transformation ◽  
Stable Property ◽  
Finite Dimensional ◽  
Finite Dimensional Distribution ◽  
Exchangeable Sequence ◽  
Dimensional Distribution

An exchangeable sequence of random variables is constructed with all finite-dimensional distribution functions having an Archimedean copula (as defined by Schweizer and Sklar (1983)). Through a monotone transformation of this exchangeable sequence, we obtain and characterize the class of exchangeable sequences possessing the max-stable property as defined by De Haan and Rachev (1989). Several parametric examples are given.

scholarly journals Fitting Compound Archimedean Copulas to Data for Modeling Electricity Demand

2021 ◽  
Vol 10 (5) ◽  
pp. 20
Author(s):  
Moshe Kelner ◽  
Zinoviy Landsman ◽  
Udi E. Makov
Keyword(s):  
Random Variables ◽  
Electricity Demand ◽  
Archimedean Copula ◽  
Dependence Structure ◽  
Archimedean Copulas ◽  
Copula Functions ◽  
Maximum Daily Temperature ◽  
Multiple Parameter ◽  
Original Family ◽  
Dependence Structures

Modeling dependence between random variables is accomplished effectively by using copula functions. Practitioners often rely on the single parameter Archimedean family which contains a large number of functions, exhibiting a variety of dependence structures. In this work we propose the use of the multiple-parameter compound Archimedean family, which extends the original family and allows more elaborate dependence structures. In particular, we use a copula of this type to model the dependence structure between the minimum daily electricity demand and the maximum daily temperature. It is shown that the compound Archimedean copula enhances the flexibility of the dependence structure and provides a better fit to the data.

Archimedean copulas, exchangeability, and max-stability

1994 ◽  
Vol 31 (02) ◽  
pp. 383-390 ◽  
Author(s):  
Rocco Ballerini
Keyword(s):  
Random Variables ◽  
Distribution Functions ◽  
Archimedean Copula ◽  
Archimedean Copulas ◽  
Monotone Transformation ◽  
Stable Property ◽  
Finite Dimensional ◽  
Finite Dimensional Distribution ◽  
Exchangeable Sequence ◽  
Dimensional Distribution

An exchangeable sequence of random variables is constructed with all finite-dimensional distribution functions having an Archimedean copula (as defined by Schweizer and Sklar (1983)). Through a monotone transformation of this exchangeable sequence, we obtain and characterize the class of exchangeable sequences possessing the max-stable property as defined by De Haan and Rachev (1989). Several parametric examples are given.

Hydrogeological responses in tropical mountainous springs

2019 ◽  
Author(s):  
Ricardo Sánchez-Murillo
Keyword(s):  
Costa Rica ◽  
Isotope Composition ◽  
Central Valley ◽  
Distribution Functions ◽  
Geochemical Composition ◽  
Transit Times ◽  
Management Plans ◽  
Best Fit ◽  
Term Data

This study presents a hydrogeochemical analysis of spring responses (2013-2017) in the tropical mountainous region of the Central Valley of Costa Rica. The isotopic distribution of δ18O and δ2H in rainfall resulted in a highly significant meteoric water line: δ2H = 7.93×δ18O + 10.37 (r2=0.97). Rainfall isotope composition exhibited a strong dependent seasonality. The isotopic variation (δ18O) of two springs within the Barva aquifer was simulated using the FlowPC program to determine mean transit times (MTTs). Exponential-piston and dispersion distribution functions provided the best-fit to the observed isotopic composition at Flores and Sacramento springs, respectively. MTTs corresponded to 1.23±0.03 (Sacramento) and 1.42±0.04 (Flores) years. The greater MTT was represented by a homogeneous geochemical composition at Flores, whereas the smaller MTT at Sacramento is reflected in a more variable geochemical response. The results may be used to enhance modelling efforts in central Costa Rica, whereby scarcity of long-term data limits water resources management plans.

scholarly journals Spatio-temporal expectile regression models

2019 ◽  
Vol 20 (4) ◽  
pp. 386-409
Author(s):  
Elmar Spiegel ◽  
Thomas Kneib ◽  
Fabian Otto-Sobotka
Keyword(s):  
Tensor Product ◽  
Least Squares Regression ◽  
Expectile Regression ◽  
Specific Distribution ◽  
Weighted Means ◽  
Temporal Models ◽  
Error Terms ◽  
Spatio Temporal ◽  
Set Up ◽  
Main Effects

Spatio-temporal models are becoming increasingly popular in recent regression research. However, they usually rely on the assumption of a specific parametric distribution for the response and/or homoscedastic error terms. In this article, we propose to apply semiparametric expectile regression to model spatio-temporal effects beyond the mean. Besides the removal of the assumption of a specific distribution and homoscedasticity, with expectile regression the whole distribution of the response can be estimated. For the use of expectiles, we interpret them as weighted means and estimate them by established tools of (penalized) least squares regression. The spatio-temporal effect is set up as an interaction between time and space either based on trivariate tensor product P-splines or the tensor product of a Gaussian Markov random field and a univariate P-spline. Importantly, the model can easily be split up into main effects and interactions to facilitate interpretation. The method is presented along the analysis of spatio-temporal variation of temperatures in Germany from 1980 to 2014.

scholarly journals Diffusion at the Earth magnetopause: enhancement by Kelvin-Helmholtz instability

2007 ◽  
Vol 25 (1) ◽  
pp. 271-282 ◽  
Author(s):  
R. Smets ◽  
G. Belmont ◽  
D. Delcourt ◽  
L. Rezeau
Keyword(s):  
Magnetic Field ◽  
Distribution Functions ◽  
Larmor Radius ◽  
Simple Analytical Model ◽  
Helmholtz Instability ◽  
Field Reversal ◽  
Finite Larmor Radius ◽  
The Earth ◽  
Specific Distribution ◽  
The Magnetic Field

Abstract. Using hybrid simulations, we examine how particles can diffuse across the Earth's magnetopause because of finite Larmor radius effects. We focus on tangential discontinuities and consider a reversal of the magnetic field that closely models the magnetopause under southward interplanetary magnetic field. When the Larmor radius is on the order of the field reversal thickness, we show that particles can cross the discontinuity. We also show that with a realistic initial shear flow, a Kelvin-Helmholtz instability develops that increases the efficiency of the crossing process. We investigate the distribution functions of the transmitted ions and demonstrate that they are structured according to a D-shape. It accordingly appears that magnetic reconnection at the magnetopause is not the only process that leads to such specific distribution functions. A simple analytical model that describes the built-up of these functions is proposed.

The Palomar-Leiden Survey

1971 ◽  
Vol 12 ◽  
pp. 183-186
Author(s):  
C.J. Van Houten
Keyword(s):  
Semimajor Axis ◽  
Continuous Extension ◽  
Distribution Functions ◽  
Set Up

The Palomar-Leiden survey (PLS) was set up as an extension to fainter magnitudes of the McDonald survey. The latter is, therefore, the more important survey as far as asteroid statistics are concerned. The main result of the PLS is that no clearcut differences exist between the fainter asteroids found in this survey and the numbered asteroids in the distribution functions of eccentricity, inclination, and semimajor axis and that the statistical relations found in the McDonald survey have a continuous extension in the PLS material. I would, therefore, propose not to summarize the results of the PLS, which would appear to be a tedious job, but to give here some new results that should properly have been included in the publication, but, for reasons of pressures to publish as soon as possible, were not.

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