Zobrazeno 1 - 10
of 157
pro vyhledávání: '"62G07, 62G20"'
Autor:
Maillet, Raphaël, Szymanski, Grégoire
We introduce a new approach for estimating the invariant density of a multidimensional diffusion when dealing with high-frequency observations blurred by independent noises. We consider the intermediate regime, where observations occur at discrete ti
Externí odkaz:
http://arxiv.org/abs/2404.12181
Autor:
Penda, S. Valère Bitseki
We study the kernel estimator of the transition density of bifurcating Markov chains. Under some ergodic and regularity properties, we prove that this estimator is consistent and asymptotically normal. Next, in the numerical studies, we propose two d
Externí odkaz:
http://arxiv.org/abs/2303.15064
Autor:
Seck, Cheikh Tidiane, Mamane, Salha
In this paper, we investigate the almost sure convergence, in supremum norm, of the rank-based linear wavelet estimator for a multivariate copula density. Based on empirical process tools, we prove a uniform limit law for the deviation, from its expe
Externí odkaz:
http://arxiv.org/abs/2303.05627
Autor:
Wang, Sven, Marzouk, Youssef
We study the convergence properties, in Hellinger and related distances, of nonparametric density estimators based on measure transport. These estimators represent the measure of interest as the pushforward of a chosen reference distribution under a
Externí odkaz:
http://arxiv.org/abs/2207.10231
We study the Bayesian density estimation of data living in the offset of an unknown submanifold of the Euclidean space. In this perspective, we introduce a new notion of anisotropic H\"older for the underlying density and obtain posterior rates that
Externí odkaz:
http://arxiv.org/abs/2205.15717
Publikováno v:
Journal of Nonparametric Statistics, 2022
Discrete kernel smoothing is now gaining importance in nonparametric statistics. In this paper, we investigate some asymptotic properties of the normalized discrete associated-kernel estimator of a probability mass function. We show, under some regul
Externí odkaz:
http://arxiv.org/abs/2202.10078
Autor:
Nogales, A. G.
Under mild conditions, it is shown the strong consistency of the Bayes estimator of the density. Moreover, the Bayes risk (for some common loss functions) of the Bayes estimator of the density (i.e. the posterior predictive density) reaches zero when
Externí odkaz:
http://arxiv.org/abs/2110.13081
Autor:
Pastukhov, Vladimir
In this paper we consider the stacking of isotonic regression and the method of rearrangement with the empirical estimator to estimate a discrete distribution with an infinite support. The estimators are proved to be strongly consistent with $\sqrt{n
Externí odkaz:
http://arxiv.org/abs/2106.00560
Publikováno v:
Stats 2021, 4(1), 162-183
Multivariate nonnegative orthant data are real vectors bounded to the left by the null vector, and they can be continuous, discrete or mixed. We first review the recent relative variability indexes for multivariate nonnegative continuous and count di
Externí odkaz:
http://arxiv.org/abs/2101.08365
Autor:
Goldenshluger, Alexander, Kim, Taeho
It is a typical standard assumption in the density deconvolution problem that the characteristic function of the measurement error distribution is non-zero on the real line. While this condition is assumed in the majority of existing works on the top
Externí odkaz:
http://arxiv.org/abs/2101.02491