Results 221 to 230 of about 6,398 (252)

Nonparametric Estimation of Multivariate Density and its Derivative by Dependent Data Using Gamma Kernels

Journal of Mathematical Sciences, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Nonparametric estimation of the ratios of derivatives of a multivariate distribution density from dependent observations

Siberian Mathematical Journal, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vasil'ev, V. A., Koshkin, G. M.
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A Transformation-Based Nonparametric Estimator of Multivariate Densities with an Application to Global Financial Markets

SSRN Electronic Journal, 2011
We propose a probability-integral-transformation-based estimator of multivariate densities. Given a sample of random vectors, we rst transform the data into their corresponding marginal distributions. We then estimate the density of the transformed data via the Exponential Series Estimator in Wu (2010).
Meng-Shiuh Chang, Ximing Wu
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Nonparametric method for estimating spoken language sound multivariate probability density function

2008 Microwaves, Radar and Remote Sensing Symposium, 2008
In the paper a new approach for estimating of the spoken language sound multivariate probability density is suggested. It is based on the use of a projection of a random process to the set of random variables, with the probability density defined as a product of two-dimensional densities.
Zanna M. Bokal, Rustem B. Sinitsyn
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A Note on Asymptotic Behavior of the Nonparametric Density Estimators in Multivariate Mixtures

Communications in Statistics - Theory and Methods, 2009
The asymptotic behavior of the nonparametric density estimator has been given for a multivariate mixture model. It has been observed that the estimator is asymptotically normally distributed with bias of size h 2 and variance of size (nh)−1.
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Speed of convergence in nonparametric estimation of a multivariate μ-density and its mixed partial derivatives

Journal of Statistical Planning and Inference, 1981
Abstract Let f be a m-variate unknown density with respect to a σ-finite measure on Em, the m- dimensional Euclidean space, and let x=(x1,…,xm) and p=(p1,…,pm) be in Em, where p j≥0 are arbitrary integers. This paper exhibits kernel estimators of mixed partial derivatives f (p) (x)=(∂ p 1 +…+p m f ∂(x))/(∂x P1 1 …∂x
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A new approach to nonparametric estimation of multivariate spectral density function using basis expansion

Computational Statistics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shirin Nezampour, Alireza Nematollahi, Robert T. Krafty, Mehdi Maadooliat   +3 more
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Central limit theorem for square error of multivariate nonparametric box spline density estimators

Applicationes Mathematicae, 2001
Summary: We prove the central limit theorem for the integrated square error of multivariate box-spline density estimators.
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Nonparametric Probability Density Estimation: I. A Summary of Available Methods

Technometrics, 1972
Edward J Wegman
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Density Distillation for Fast Nonparametric Density Estimation

IEEE Transactions on Neural Networks and Learning Systems, 2023
Bopeng Fang, Shifeng Chen
exaly