Results 11 to 20 of about 106 (99)
On the use of L-functionals in regression models
Open Mathematics, 2023 In this article, we survey and unify a large class or LL-functionals of the conditional distribution of the response variable in regression models.
Hössjer Ola, Karlsson Måns
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Sequential change-point detection in a multinomial logistic regression model
Open Mathematics, 2020 Change-point detection in categorical time series has recently gained attention as statistical models incorporating change-points are common in practice, especially in the area of biomedicine.
Li Fuxiao, Chen Zhanshou, Xiao Yanting
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Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case
Dependence Modeling, 2021 Given a d-dimensional random vector X = (X1, . . ., Xd), if the standard uniform vector U obtained by the component-wise probability integral transform (PIT) of X has the same distribution of its point reflection through the center of the unit hypercube,
Billio Monica +2 more
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Dependence Modeling, 2021 Consider a survival time study, where a sequence of possibly censored failure times is observed with d-dimensional covariate The main goal of this article is to establish the asymptotic normality of the kernel estimator of the relative error regression ...
Bouhadjera Feriel, Saïd Elias Ould
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Dispersive order comparisons on extreme order statistics from homogeneous dependent random vectors
Dependence Modeling, 2021 In this paper, we investigate sufficient conditions for preservation property of the dispersive order for the smallest and largest order statistics of homogeneous dependent random vectors.
Mesfioui Mhamed, Trufin Julien
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Goodness-of-Fit Tests in Nonparametric Regression [PDF]
, 2006 AMS classifications: 62G08, 62G10, 62G20, 62G30 ...
John H. J. Einmahl +3 more
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On the approximation of an integral by a sum of random variables
International Journal of Stochastic Analysis, Volume 11, Issue 2, Page 107-114, 1998., 1997 We approximate the integral of a smooth function on [0, 1], where values are only known at n random points (i.e., a random sample from the uniform‐(0, 1) distribution), and at 0 and 1. Our approximations are based on the trapezoidal rule and Simpson′s rule (generalized to the non‐equidistant case), respectively.
John H. J. Einmahl +1 more
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Laws of large numbers for L‐statistics
International Journal of Stochastic Analysis, Volume 7, Issue 2, Page 125-143, 1994., 1994 Consider Ln = n−1∑1≤i≤ncnig(Xn:i) for order statistics Xn:i and let for some (Lebesgue) λ‐summable over (0, 1) function J. Sufficient as well as necessary conditions for to hold almost surely and in probability are given. Superposition (or Nemytskii) operators have been used to derive the laws of large numbers for L‐statistics from the laws of large ...
Rimas Norvaiša
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Bootstrap variance estimation for Nadaraya quantile estimator [PDF]
, 2009 Nadaraya quantile estimator, Order-calibration, Smoothed bootstrap, 62G05, 62G09, 62G30,
Cheung, KY +5 more
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Various limit theorems for ratios from the uniform distribution
Open Mathematics, 2016 In this paper, we consider the ratios of order statistics in samples from uniform distribution and establish strong and weak laws for these ratios.
Miao Yu, Sun Yan, Wang Rujun, Dong Manru
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