Gram–Charlier densities: a multivariate approach
نویسندگان
چکیده
منابع مشابه
Cross -Validation of Multivariate Densities
In recent years, the focus of study in smoothing parameter selection for kernel density estimation has been on the univariate case, while multivariate kernel density estimation has been largely neglected. In part, this may be due to the perception that calibrating multivariate densities is substantially more diicult. In this paper, we explicitly derive and compare multivariate versions of the b...
متن کاملSampling from Linear Multivariate Densities
It is well known that the generation of random vectors with nonindependent components is difficult. Nevertheless, we propose a new and very simple generation algorithm for multivariate linear densities over point-symmetric domains. Among other applications it can be used to design a simple decompositionrejection algorithm for multivariate concave distributions.
متن کاملNonparametric Estimation of Multivariate Convex-transformed Densities.
We study estimation of multivariate densities p of the form p(x) = h(g(x)) for x ∈ ℝ(d) and for a fixed monotone function h and an unknown convex function g. The canonical example is h(y) = e(-y) for y ∈ ℝ; in this case, the resulting class of densities [Formula: see text]is well known as the class of log-concave densities. Other functions h allow for classes of densities with heavier tails tha...
متن کاملTransformation-based nonparametric estimation of multivariate densities
We propose a probability-integral-transformation-based estimator of multivariate densities. We first transform multivariate data into their corresponding marginal distributions. The marginal densities and the joint density of the transformed data are estimated nonparametrically. The density of the original data is constructed as the product of the density of transformed data and that of the mar...
متن کاملOptimal Reduction of Multivariate Dirac Mixture Densities
This paper is concerned with the optimal approximation of a given multivariate Dirac mixture, i.e., a density comprising weighted Dirac distributions on a continuous domain, by an equally weighted Dirac mixture with a reduced number of components. The parameters of the approximating density are calculated by minimizing a smooth global distance measure, a generalization of the well-known Cramér-...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Quantitative Finance
سال: 2009
ISSN: 1469-7688,1469-7696
DOI: 10.1080/14697680902773611