The Experts below are selected from a list of 23283 Experts worldwide ranked by ideXlab platform
Koen Decancq - One of the best experts on this subject based on the ideXlab platform.
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elementary multivariate rearrangements and stochastic dominance on a frechet class
Journal of Economic Theory, 2012Co-Authors: Koen DecancqAbstract:A Frechet class collects all multivariate Joint Distribution Functions that have the same marginals. Members of a Frechet class only differ with respect to the interdependence between their marginals. In this paper, I study orders of interdependence on a Frechet class using two multivariate generalizations of the bivariate rearrangement proposed by Epstein and Tanny (1980) [4] and Tchen (1980) [16]. I show how these multivariate rearrangements are underlying multivariate first order stochastic dominance in terms of the Joint Distribution Function and the survival Function. A combination of both rearrangements is shown to be equivalent to the concordance order proposed by Joe (1990.
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elementary multivariate rearrangements and stochastic dominance on a frechet class
LIDAM Reprints CORE, 2012Co-Authors: Koen DecancqAbstract:A Frechet class collects all multivariate Joint Distribution Functions that have the same marginals. Members of a Frechet class only differ with respect to the interdependence between their marginals. In this paper, I study orders of interdependence on a Frechet class using two multivariate generalizations of the bivariate rearrangement proposed by Epstein and Tanny (1980) [4] and Tchen (1980) [16]. I show how these multivariate rearrangements are underlying multivariate first order stochastic dominance in terms of the Joint Distribution Function and the survival Function. A combination of both rearrangements is shown to be equivalent to the concordance order proposed by Joe (1990) [9].(This abstract was borrowed from another version of this item.)
J Hanus - One of the best experts on this subject based on the ideXlab platform.
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shape and spin Distributions of asteroid populations from brightness variation estimates and large databases
Astronomy and Astrophysics, 2017Co-Authors: H Nortunen, M Kaasalainen, J ďurech, H Cibulkova, Victor Alilagoa, J HanusAbstract:Context. Many databases on asteroid brightnesses (e.g. ALCDEF, WISE) are potential sources for extensive asteroid shape and spin modelling. Individual lightcurve inversion models require several apparitions and hundreds of data points per target. However, we can analyse the coarse shape and spin Distributions over populations of at least thousands of targets even if there are only a few points and one apparition per asteroid. This is done by examining the Distribution of the brightness variations observed within the chosen population.Aims. Brightness variation has been proposed as a population-scale rather than individual-target observable in two studies so far. We aim to examine this approach rigorously to establish its theoretical validity, degree of ill-posedness, and practical applicability.Methods. We model the observed brightness variation of a target population by considering its cumulative Distribution Function (CDF) caused by the Joint Distribution Function of two fundamental shape and spin indicators. These are the shape elongation and the spin latitude of a simple ellipsoidal model. The main advantage of the model is that we can derive analytical basis Functions that yield the observed CDF as a Function of the shape and spin Distribution. The inverse problem can be treated linearly. Even though the inaccuracy of the model is considerable, databases of thousands of targets should yield some information on the Distribution. We employ numerical simulations to establish this and analyse photometric databases that provide sufficiently large numbers of data points for reliable brightness variation estimates.Results. We establish the theoretical soundness and the typical accuracy limits of the approach both analytically and numerically. We propose a robust brightness variation observable η based on at least five brightness points per target. We also discuss the weaker reliability and information content of the case of only two points per object. Using simulations, we derive a practical estimate of the model Distribution in the (shape, spin)-plane. We show that databases such as Wide-field Infrared Survey Explorer (WISE) yield coarse but robust estimates of this Distribution, and as an example compare various asteroid families with each other.
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shape and spin Distributions of asteroid populations from brightness variation estimates and large databases
arXiv: Earth and Planetary Astrophysics, 2017Co-Authors: H Nortunen, M Kaasalainen, J ďurech, H Cibulkova, Victor Alilagoa, J HanusAbstract:Context. Many databases on asteroid brightnesses (e.g. ALCDEF, WISE) are potential sources for extensive asteroid shape and spin modelling. Individual lightcurve inversion models require several apparitions and hundreds of data points per target. However, we can analyse the coarse shape and spin Distributions over populations of at least thousands of targets even if there are only a few points and one apparition per asteroid. This is done by examining the Distribution of the brightness variations observed within the chosen population. Aims. Brightness variation has been proposed as a population-scale rather than individual-target observable in two studies so far. We aim to examine this approach rigorously to establish its theoretical validity, degree of ill-posedness, and practical applicability. Methods. We model the observed brightness variation of a target population by considering its cumulative Distribution Function (CDF) caused by the Joint Distribution Function of two fundamental shape and spin indicators. These are the shape elongation and the spin latitude of a simple ellipsoidal model. The main advantage of the model is that we can derive analytical basis Functions that yield the observed CDF as a Function of the shape and spin Distribution. The inverse problem can be treated linearly. Even though the inaccuracy of the model is considerable, databases of thousands of targets should yield some information on the Distribution. Results. We establish the theoretical soundness and the typical accuracy limits of the approach both analytically and numerically. Using simulations, we derive a practical estimate of the model Distribution in the (shape, spin)-plane. We show that databases such as Wide-field Infrared Survey Explorer (WISE) yield coarse but robust estimates of this Distribution, and as an example compare various asteroid families with each other.
Xi Chen - One of the best experts on this subject based on the ideXlab platform.
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assessing environmental water requirement for groundwater dependent vegetation in arid inland basins by combining the copula Joint Distribution Function and the dual objective optimization an application to the turpan basin china
Science of The Total Environment, 2021Co-Authors: Feng Huang, Carlos Ochoa, Xi ChenAbstract:Abstract Preserving groundwater-dependent terrestrial ecosystems through environmental water allocation is critical for sustainable development in arid inland basins. Assessing the environmental water requirement is challenging due to the complex relationship between vegetation growth and groundwater depth. This study proposed a new assessment method by combining the copula Joint Distribution Function and the dual objective optimization. The copula Joint Distribution Function was used to describe the relationship between vegetation and groundwater depth instead of the traditional regression analysis. Given an ecological protection target, the conditional probability of achieving the target was estimated using the copula Joint Distribution. The groundwater depth interval with relatively high probability was suitable for vegetation growth and correspondingly conducive for ecological protection. In addition to ecological protection, the socio-economic water requirement was incorporated into the environmental water assessment, resulting in a dual optimization problem that could be resolved by the ideal point method. The optimization analysis revealed a groundwater depth with a high probability of successful ecological protection and low groundwater evapotranspiration to balance vegetation and human demands for groundwater. The proposed method of environmental water assessment by combing copula Joint Distribution Function and dual objective optimization was applied in the Turpan Basin, an arid inland basin in Northwest China. The environmental groundwater depth ranged between 6 and 20 m, and the optimized interval was 7–8 m. The optimal environmental groundwater depth resulted in a probability of 0.46 to achieve the ecological protection target and annual evapotranspiration of 983 mm. The proposed method was practical and reliable and could be an effective tool for assessing the environmental water requirement of groundwater-dependent vegetation in arid inland basins.
H Nortunen - One of the best experts on this subject based on the ideXlab platform.
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shape and spin Distributions of asteroid populations from brightness variation estimates and large databases
Astronomy and Astrophysics, 2017Co-Authors: H Nortunen, M Kaasalainen, J ďurech, H Cibulkova, Victor Alilagoa, J HanusAbstract:Context. Many databases on asteroid brightnesses (e.g. ALCDEF, WISE) are potential sources for extensive asteroid shape and spin modelling. Individual lightcurve inversion models require several apparitions and hundreds of data points per target. However, we can analyse the coarse shape and spin Distributions over populations of at least thousands of targets even if there are only a few points and one apparition per asteroid. This is done by examining the Distribution of the brightness variations observed within the chosen population.Aims. Brightness variation has been proposed as a population-scale rather than individual-target observable in two studies so far. We aim to examine this approach rigorously to establish its theoretical validity, degree of ill-posedness, and practical applicability.Methods. We model the observed brightness variation of a target population by considering its cumulative Distribution Function (CDF) caused by the Joint Distribution Function of two fundamental shape and spin indicators. These are the shape elongation and the spin latitude of a simple ellipsoidal model. The main advantage of the model is that we can derive analytical basis Functions that yield the observed CDF as a Function of the shape and spin Distribution. The inverse problem can be treated linearly. Even though the inaccuracy of the model is considerable, databases of thousands of targets should yield some information on the Distribution. We employ numerical simulations to establish this and analyse photometric databases that provide sufficiently large numbers of data points for reliable brightness variation estimates.Results. We establish the theoretical soundness and the typical accuracy limits of the approach both analytically and numerically. We propose a robust brightness variation observable η based on at least five brightness points per target. We also discuss the weaker reliability and information content of the case of only two points per object. Using simulations, we derive a practical estimate of the model Distribution in the (shape, spin)-plane. We show that databases such as Wide-field Infrared Survey Explorer (WISE) yield coarse but robust estimates of this Distribution, and as an example compare various asteroid families with each other.
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shape and spin Distributions of asteroid populations from brightness variation estimates and large databases
arXiv: Earth and Planetary Astrophysics, 2017Co-Authors: H Nortunen, M Kaasalainen, J ďurech, H Cibulkova, Victor Alilagoa, J HanusAbstract:Context. Many databases on asteroid brightnesses (e.g. ALCDEF, WISE) are potential sources for extensive asteroid shape and spin modelling. Individual lightcurve inversion models require several apparitions and hundreds of data points per target. However, we can analyse the coarse shape and spin Distributions over populations of at least thousands of targets even if there are only a few points and one apparition per asteroid. This is done by examining the Distribution of the brightness variations observed within the chosen population. Aims. Brightness variation has been proposed as a population-scale rather than individual-target observable in two studies so far. We aim to examine this approach rigorously to establish its theoretical validity, degree of ill-posedness, and practical applicability. Methods. We model the observed brightness variation of a target population by considering its cumulative Distribution Function (CDF) caused by the Joint Distribution Function of two fundamental shape and spin indicators. These are the shape elongation and the spin latitude of a simple ellipsoidal model. The main advantage of the model is that we can derive analytical basis Functions that yield the observed CDF as a Function of the shape and spin Distribution. The inverse problem can be treated linearly. Even though the inaccuracy of the model is considerable, databases of thousands of targets should yield some information on the Distribution. Results. We establish the theoretical soundness and the typical accuracy limits of the approach both analytically and numerically. Using simulations, we derive a practical estimate of the model Distribution in the (shape, spin)-plane. We show that databases such as Wide-field Infrared Survey Explorer (WISE) yield coarse but robust estimates of this Distribution, and as an example compare various asteroid families with each other.
George Y Wong - One of the best experts on this subject based on the ideXlab platform.
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consistency of the generalized mle of a Joint Distribution Function with multivariate interval censored data
Journal of Multivariate Analysis, 2006Co-Authors: George Y WongAbstract:Wong and Yu [Generalized MLE of a Joint Distribution Function with multivariate interval-censored data, J. Multivariate Anal. 69 (1999) 155-166] discussed generalized maximum likelihood estimation of the Joint Distribution Function of a multivariate random vector whose coordinates are subject to interval censoring. They established uniform consistency of the generalized MLE (GMLE) of the Distribution Function under the assumption that the random vector is independent of the censoring vector and that both of the vector Distributions are discrete. We relax these assumptions and establish consistency results of the GMLE under a multivariate mixed case interval censorship model. van der Vaart and Wellner [Preservation theorems for Glivenko-Cantelli and uniform Glivenko-Cantelli class, in: E. Gine, D.M. Mason, J.A. Wellner (Eds.), High Dimensional Probability, vol. II, Birkhauser, Boston, 2000, pp. 115-133] and Yu [Consistency of the generalized MLE with multivariate mixed case interval-censored data, Ph.D Dissertation, Binghamton University, 2000] independently proved strong consistency of the GMLE in the L"1(@m)-topology, where @m is a measure derived from the Joint Distribution of the censoring variables. We establish strong consistency of the GMLE in the topologies of weak convergence and pointwise convergence, and eventually uniform convergence under appropriate Distributional assumptions and regularity conditions.
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estimation of a Joint Distribution Function with multivariate interval censored data when the nonparametric mle is not unique
Biometrical Journal, 2000Co-Authors: George Y WongAbstract:A nonparametric estimator of a Joint Distribution Function F 0 of a d-dimensional random vector with interval-censored (IC) data is the generalized maximum likelihood estimator (GMLE), where d > 2. The GMLE of F 0 with univariate IC data is uniquely defined at each follow-up time. However, this is no longer true in general with multivariate IC data as demonstrated by a data set from an eye study. How to estimate the survival Function and the covariance matrix of the estimator in such a case is a new practical issue in analyzing IC data. We propose a procedure in such a situation and apply it to the data set from the eye study. Our method always results in a GMLE with a nonsingular sample information matrix. We also give a theoretical justification for such a procedure. Extension of our procedure to Cox's regression model is also mentioned.
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generalized mle of a Joint Distribution Function with multivariate interval censored data
Journal of Multivariate Analysis, 1999Co-Authors: George Y WongAbstract:We consider the problem of estimation of a Joint Distribution Function of a multivariate random vector with interval-censored data. The generalized maximum likelihood estimator of the Distribution Function is studied and its consistency and asymptotic normality are established under the case 2 multivariate interval censorship model and discrete assumptions on the censoring random vectors.
