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A note on almost sure convergence and convergence in measure

P. Kříž, Josef Štěpán (2014)

Commentationes Mathematicae Universitatis Carolinae

The present article studies the conditions under which the almost everywhere convergence and the convergence in measure coincide. An application in the statistical estimation theory is outlined as well.

A note on Poisson approximation.

Paul Deheuvels (1985)

Trabajos de Estadística e Investigación Operativa

We obtain in this note evaluations of the total variation distance and of the Kolmogorov-Smirnov distance between the sum of n random variables with non identical Bernoulli distributions and a Poisson distribution. Some of our results precise bounds obtained by Le Cam, Serfling, Barbour and Hall.It is shown, among other results, that if p1 = P (X1=1), ..., pn = P (Xn=1) satisfy some appropriate conditions, such that p = 1/n Σipi → 0, np → ∞, np2 → 0, then the total variation distance between X1+...+Xn...

A note on Poisson approximation by w-functions

M. Majsnerowska (1998)

Applicationes Mathematicae

One more method of Poisson approximation is presented and illustrated with examples concerning binomial, negative binomial and hypergeometric distributions.

A note on quenched moderate deviations for Sinai’s random walk in random environment

Francis Comets, Serguei Popov (2004)

ESAIM: Probability and Statistics

We consider the continuous time, one-dimensional random walk in random environment in Sinai’s regime. We show that the probability for the particle to be, at time t and in a typical environment, at a distance larger than t a ( 0 < a < 1 ) from its initial position, is exp { - Const · t a / [ ( 1 - a ) ln t ] ( 1 + o ( 1 ) ) } .

A note on quenched moderate deviations for Sinai's random walk in random environment

Francis Comets, Serguei Popov (2010)

ESAIM: Probability and Statistics

We consider the continuous time, one-dimensional random walk in random environment in Sinai's regime. We show that the probability for the particle to be, at time t and in a typical environment, at a distance larger than ta (0<a<1) from its initial position, is exp{-Const ⋅ ta/[(1 - a)lnt](1 + o(1))}.

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