77,450 research outputs found
Broad distribution effects in sums of lognormal random variables
The lognormal distribution describing, e.g., exponentials of Gaussian random
variables is one of the most common statistical distributions in physics. It
can exhibit features of broad distributions that imply qualitative departure
from the usual statistical scaling associated to narrow distributions.
Approximate formulae are derived for the typical sums of lognormal random
variables. The validity of these formulae is numerically checked and the
physical consequences, e.g., for the current flowing through small tunnel
junctions, are pointed out.Comment: 14 pages, 9 figures. Minor changes + Gini coefficient and 4 refs.
adde
Wave modelling - the state of the art
This paper is the product of the wave modelling community and it tries to make a picture of the present situation in this branch of science, exploring the previous and the most recent results and looking ahead towards the solution of the problems we presently face. Both theory and applications are considered.
The many faces of the subject imply separate discussions. This is reflected into the single sections, seven of them, each dealing with a specific topic, the whole providing a broad and solid overview of the present state of the art. After an introduction framing the problem and the approach we followed, we deal in sequence with the following subjects: (Section) 2, generation by wind; 3, nonlinear interactions in deep water; 4, white-capping dissipation; 5, nonlinear interactions in shallow water; 6, dissipation at the sea bottom; 7, wave propagation; 8, numerics. The two final sections, 9 and 10, summarize the present situation from a general point of view and try to look at the future developments
The inverse of the star-discrepancy problem and the generation of pseudo-random numbers
The inverse of the star-discrepancy problem asks for point sets of
size in the -dimensional unit cube whose star-discrepancy
satisfies where
is a constant independent of and . The first existence results in this
direction were shown by Heinrich, Novak, Wasilkowski, and Wo\'{z}niakowski in
2001, and a number of improvements have been shown since then. Until now only
proofs that such point sets exist are known. Since such point sets would be
useful in applications, the big open problem is to find explicit constructions
of suitable point sets .
We review the current state of the art on this problem and point out some
connections to pseudo-random number generators
Construction of weakly CUD sequences for MCMC sampling
In Markov chain Monte Carlo (MCMC) sampling considerable thought goes into
constructing random transitions. But those transitions are almost always driven
by a simulated IID sequence. Recently it has been shown that replacing an IID
sequence by a weakly completely uniformly distributed (WCUD) sequence leads to
consistent estimation in finite state spaces. Unfortunately, few WCUD sequences
are known. This paper gives general methods for proving that a sequence is
WCUD, shows that some specific sequences are WCUD, and shows that certain
operations on WCUD sequences yield new WCUD sequences. A numerical example on a
42 dimensional continuous Gibbs sampler found that some WCUD inputs sequences
produced variance reductions ranging from tens to hundreds for posterior means
of the parameters, compared to IID inputs.Comment: Published in at http://dx.doi.org/10.1214/07-EJS162 the Electronic
Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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