Results 41 to 50 of about 18,318 (97)

Nonparametric Density Estimation in a Mixed Model Using Wavelets

Axioms
This paper investigates nonparametric estimations of a density function within a mixed density model. A linear wavelet density estimator and an adaptive nonlinear wavelet estimator are proposed using wavelet method and hard thresholding algorithm.
Dan Liang, Junke Kou
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On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices. [PDF]

PLoS ONE, 2017
A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper.
Ke Wang, Xin Ye, Ram M Pendyala, Yajie Zou   +3 more
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Comparative Evaluation of Nonparametric Density Estimators for Gaussian Mixture Models with Clustering Support

Axioms
The article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density ...
Tomas Ruzgas, Gintaras Stankevičius, Birutė Narijauskaitė, Jurgita Arnastauskaitė Zencevičienė   +3 more
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Nonparametric density estimation of continuous part of a mixed measure

Statistica, 2007
We consider a pair of random variables(X,Y) whose probability measure is the sum of an absolutely continuous measure, a discrete measure and a finite number of absolutely continuous measures on several lines(1).
Rachid Sabre
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Nonparametric Method for Modeling Clustering Phenomena in Emergency Calls Under Spatial-Temporal Self-Exciting Point Processes

IEEE Access, 2019
In this paper, a nonparametric spatial-temporal self-exciting point process is proposed to model clustering features in emergency calls. Gaussian kernel density functions are considered.
Chenlong Li, Zhanjie Song, Xu Wang
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Nonparametric density estimation using a multidimensional mixture model of Gaussian distributions

Lietuvos Matematikos Rinkinys, 2005
This paper algorithmically and empirically studies five major types of nonparametric multivariate density estimation techniques, where no assumption is made about data being drawn from any of known parametric families of distribution. There is developed
Tomas Ruzgas, Mindaugas Kavaliauskas
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Empirical Density Estimation for Interval Censored Data

Austrian Journal of Statistics, 2016
This paper is concerned with the nonparametric estimation of a density function when the data are incomplete due to interval censoring. The Nadaraya-Watson kernel density estimator is modified to allow description of such interval data.
Eugenia Stoimenova
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Probability density estimation using data projection

Lietuvos Matematikos Rinkinys, 2009
Nonparametric estimation of multivariate multimodal probability density is analysed. The projection pursuit density estimator was proposed by J.H. Friedman.
Mindaugas Kavaliauskas
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Nonparametric Bayesian inference for multidimensional compound Poisson processes

Modern Stochastics: Theory and Applications, 2015
Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density $r_{0}$ and intensity $\lambda _{0}$.
Shota Gugushvili, Frank van der Meulen, Peter Spreij   +2 more
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The benchden Package: Benchmark Densities for Nonparametric Density Estimation

Journal of Statistical Software, 2012
This article describes the benchden package which implements a set of 28 example densities for nonparametric density estimation in R. In addition to the usual functions that evaluate the density, distribution and quantile functions or generate random ...
Thoralf Mildenberger, Henrike Weinert
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