A copula-based time series model for global horizontal irradiation

Müller, Alfred; Reuber, Matthias

doi:10.1016/j.ijforecast.2022.02.011

Cited by 4 publications

(2 citation statements)

References 36 publications

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“…Of note, they are increasingly used in several areas of forecasting such as portfolio optimization, water systems management, values at risk, irradiation effects, and stock price projections. Such applications are discussed in the following recent papers among others: Quintero et al [1], Kim et al [2], Sreekumar et al [3], Wang et al [4], Karmakar and Khadotra [5], Müller and Reuber [6], Sahamkhadam and Stephan [7], and Wang et al [8]. As well, a chapter of the monograph authored by Patton [9] is devoted to their use in connection with the forecasting of multiple time series.…”

Section: Introduction and Preliminary Considerations 1introductionmentioning

confidence: 99%

“…The following relationship between the joint density function of X and Y, denoted by h(•, •), and the associated copula density function c(• , •) can be readily obtained by differentiating the right-hand side of Equation (1) with respect to x and y: h(x, y) = f (x) g(y) c(F(x), G(y)) (6) where f (x) and g(y) respectively denote the marginal density functions of X and Y. Accordingly, the copula density function can be expressed as follows:…”

Section: Introduction and Preliminary Considerations 1introductionmentioning

confidence: 99%

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Nonparametric Copula Density Estimation Methodologies

Provost,

Zang

2024

Mathematics

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This paper proposes several methodologies whose objective consists of securing copula density estimates. More specifically, this aim will be achieved by differentiating bivariate least-squares polynomials fitted to Deheuvels’ empirical copulas, by making use of Bernstein’s approximating polynomials of appropriately selected orders; by differentiating linearized distribution functions evaluated at optimally spaced grid points; and by implementing the kernel density estimation technique in conjunction with a repositioning of the pseudo-observations and a certain criterion for determining suitable bandwidths. Smoother representations of such density estimates can further be secured by approximating them by means of moment-based bivariate polynomials. The various copula density estimation techniques being advocated herein are successfully applied to an actual dataset as well as a random sample generated from a known distribution.

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Section: Introduction and Preliminary Considerations 1introductionmentioning

confidence: 99%

Section: Introduction and Preliminary Considerations 1introductionmentioning

confidence: 99%

Nonparametric Copula Density Estimation Methodologies

Provost,

Zang

2024

Mathematics

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Analysis of Bayesian mixed of copulas on traffic flow using Markov chain Monte Carlo method

Marpaung,

Siringoringo,

Tarigan

2024

AIP Conference Proceedings

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Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty

Müller,

Scarsini,

Tsetlin

et al. 2023

Operations Research

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Decision with Several Objectives Under Uncertainty Important decisions typically involve multiple objectives and uncertainty. Assessing both multivariate utility and multivariate distributions for the attributes can be challenging. Moreover, big decisions are usually made by boards or committees with members holding divergent views and preferences and facing pressures from different stakeholders. Thus, a full-blown traditional decision analysis that leads to the computation of expected utility is very difficult at best and often not possible. In “Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty” Müller, Scarsini, Tsetlin, and Winkler develop sufficient conditions for multivariate almost stochastic dominance based on marginal distributions of the attributes or just on their means and variances. Such tools, consistent with normative decision analysis, are useful when making important decisions in today’s fast-moving and often complex world.

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A copula-based time series model for global horizontal irradiation

Cited by 4 publications

References 36 publications

Nonparametric Copula Density Estimation Methodologies

Nonparametric Copula Density Estimation Methodologies

Analysis of Bayesian mixed of copulas on traffic flow using Markov chain Monte Carlo method

Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty

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