Results 51 to 60 of about 15,741 (130)
Boundary Kernels for Distribution Function Estimation
Boundary effects for kernel estimators of curves with compact supports are well known in regression and density estimation frameworks. In this paper we address the use of boundary kernels for distribution function estimation.
Carlos Tenreiro
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A law of the iterated logarithm for small counts in Karlin’s occupancy scheme
In the Karlin infinite occupancy scheme, balls are thrown independently into an infinite array of boxes $1,2,\dots $ , with probability ${p_{k}}$ of hitting the box k.
Alexander Iksanov, Valeriya Kotelnikova
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Asymptotic Behaviors of the Lorenz Curve for Left Truncated and Dependent Data [PDF]
The purpose of this paper is to provide some asymptotic results for nonparametric estimator of the Lorenz curve and Lorenz process for the case in which data are assumed to be strong mixing subject to random left truncation.
M. Bolbolian Ghalibaf
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Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables [PDF]
In this paper, we obtain the upper exponential bounds for the tail probabilities of the quadratic forms for negatively dependent subgaussian random variables.
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Precise asymptotics in the law of the iterated logarithm of random fields(随机场重对数律的精确渐近性)
设{X,Xk,k ∈ Zd+,X(i),i ≥ 1}是独立同分布的随机变量序列,且EX = 0,对δ>0,E[X2(log log|X|)1+δ]
YUANYu-ze(袁裕泽)
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A Nonlinear Dynamical View of Kleiber's Law on the Metabolism of Plants and Animals. [PDF]
Camacho-Vidales LJ, Robledo A.
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In this paper, we consider the strong convergence of Lp-norms (p≥1) of a kernel estimator of a cumulative distribution function (CDF). Under some mild conditions, the law of the iterated logarithm (LIL) for the Lp-norms of empirical processes is extended
Fuxia Cheng
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Asymptotics for the Moment Convergence of
Let be a -statistic based on a symmetric kernel and i.i.d. samples . In this paper, the exact moment convergence rates in the law of the iterated logarithm and the law of the logarithm of are obtained, which extend previous results concerning ...
Fu Ke-Ang
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This paper investigates the asymptotic behavior of kernel-based estimators for the error distribution in a first-order autoregressive model with dependent errors. The model assumes that the error terms form an α-mixing sequence with an unknown cumulative
Bing Wang +4 more
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Let X={Xi,i≥1} be a sequence of real valued random variables, S0=0 and Sk=∑i=1kXi (k≥1). Let σ={σ(x),x∈Z} be a sequence of real valued random variables which are independent of X’s.
Wensheng Wang, Anwei Zhu
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