Results 81 to 90 of about 1,835 (300)
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
doaj +1 more source
Abstract Many theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek.
Anthony J. Million +3 more
wiley +1 more source
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.
doaj
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
doaj +1 more source
Abstract This ethnographic study explores vehicle residents' information practices in the United States (US). Vehicle residents are people whose primary means of housing is a vehicle. This work builds on previous research encompassing transitions and fractured (information) landscapes. Using fractured information landscapes as the theoretical framework,
Kaitlin E. Montague
wiley +1 more source
On the Multivariate Law of the Iterated Logarithm
A Hilbert space law of the iterated logarithm is proved which generalizes Kolmogorov's law for bounded random variables and which generalizes results of Teicher for unbounded random variables. The result for identically distributed random vectors is a consequence.
openaire +2 more sources
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
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
doaj
A Nonlinear Dynamical View of Kleiber's Law on the Metabolism of Plants and Animals. [PDF]
Camacho-Vidales LJ, Robledo A.
europepmc +1 more source
A note on the law of the iterated logarithm in Hilbert space [PDF]
Uwe Einmahl
openalex +1 more source

