Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where James Kuelbs is active.

Publication


Featured researches published by James Kuelbs.


Journal of Multivariate Analysis | 1973

The Invariance Principle for Banach Space Valued Random Variables

James Kuelbs

We extend the invariance principle to triangular arrays of Banach space valued random variables, and as an application derive the invariance principle for lattices of random variables. We also point out how the q-dimensional time parameter Yeh-Wiener process is naturally related to a one dimensional time Wiener process with an infinite dimensional Banach space as a state space.


Probability Theory and Related Fields | 1994

The Gaussian measure of shifted balls

James Kuelbs; Wenbo V. Li; Werner Linde

SummaryLet μ be a centered Gaussian measure on a Hilbert spaceH and let


Probability Theory and Related Fields | 1991

Rates of clustering for some Gaussian self-similar processes

Victor Goodman; James Kuelbs


Journal of Theoretical Probability | 1995

Small ball probabilities for Gaussian processes with stationary increments under Hölder norms

James Kuelbs; Wenbo V. Li; Qi-Man Shao

B_R \subseteq H


Probability Theory and Related Fields | 1983

Limit theorems for moving averages of independent random vectors

A. Acosta; James Kuelbs


Journal of Functional Analysis | 1973

Some Results for Probability Measures on Linear Topological Vector Spaces with an Application to Strassen's Log Log Law

James Kuelbs

be the centered ball of radiusR>0. Fora∈H and


Journal of Theoretical Probability | 1993

Small ball estimates for Brownian motion and the Brownian sheet

James Kuelbs; Wenbo V. Li


Journal of Theoretical Probability | 1991

Rates of clustering in Strassen's LIL for Brownian motion

Victor Goodman; James Kuelbs

\mathop {\lim }\limits_{t{\mathbf{ }} \to {\mathbf{ }}\infty } {\mathbf{ }}R(t)/t< {\mathbf{ }}||a||


Probability Theory and Related Fields | 1987

Extreme values and the law of the iterated logarithm

James Kuelbs; M. Ledoux


Annals of Statistics | 2010

ASYMPTOTIC INFERENCE FOR HIGH-DIMENSIONAL DATA

James Kuelbs; Anand N. Vidyashankar

, we give the exact asymptotics of μ(BR(t)+t·a) ast→∞. Also, upper and lower bounds are given when μ is defined on an arbitrary separable Banach space. Our results range from small deviation estimates to large deviation estimates.

Collaboration


Dive into the James Kuelbs's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Wenbo V. Li

University of Delaware

View shared research outputs
Top Co-Authors

Avatar

Victor Goodman

Indiana University Bloomington

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Wenbo Li

University of Delaware

View shared research outputs
Top Co-Authors

Avatar

Uwe Einmahl

Vrije Universiteit Brussel

View shared research outputs
Top Co-Authors

Avatar

M. Ledoux

University of Strasbourg

View shared research outputs
Researchain Logo
Decentralizing Knowledge