Searcharxiv⌕ Search

arXiv subjects

Wilfrid S. Kendall

Publications and source records attributed to Wilfrid S. Kendall.

23 records · Page 2Linked to original sources

Short-length routes in low-cost networks via Poisson line patterns

In designing a network to link n cities in a square of area n, one might be guided by the following two desiderata. First, the total network length should not be much greater than the length of the shortest network connecting all cities. Second, the average route length (taken over source-destination pairs) should not be much greater than the average straight-line distance. How small can we make these two differences? For typical configurations the shortest network length is order n and the average straight-line distance is order n^1/2, so it seems implausible that one can construct a network in which the first difference is o(n) and the second difference is o(n^1/2). But in fact one can do better: for an arbitrary configuration one can construct a network where the first difference is o(n) and the second difference is almost as small as O(log n). The construction is conceptually simple: over the minimum-length connected network (Steiner tree) superimpose a sparse stationary and isotropic Poisson line process. The key ingredient is a new result about the Poisson line process. Consider two points at distance r apart, and delete from the line process all lines which separate these two points. The resulting pattern of lines partitions the plane into cells; the cell containing the two points has mean boundary length 2r + C log r. Turning to lower bounds we show that, under a weak equidistribution assumption, if the first difference is O(n) then the second difference cannot be o(sqrt(log n)).

math.PR↗

Perfect simulation for a class of positive recurrent Markov chains

This paper generalizes the work of Kendall [Electron. Comm. Probab. 9 (2004) 140--151], which showed that perfect simulation, in the form of dominated coupling from the past, is always possible (although not necessarily practical) for geometrically ergodic Markov chains. Here, we consider the more general situation of positive recurrent chains and explore when it is possible to produce such a simulation algorithm for these chains. We introduce a class of chains which we name tame, for which we show that perfect simulation is possible.

math.PR↗

Coupling all the Lévy stochastic areas of multidimensional Brownian motion

It is shown how to construct a successful co-adapted coupling of two copies of an $n$-dimensional Brownian motion $(B_1,...,B_n)$ while simultaneously coupling all corresponding copies of Lévy stochastic areas $\int B_i dB_j-\int B_j dB_i$. It is conjectured that successful co-adapted couplings still exist when the Lévy stochastic areas are replaced by a finite set of multiply iterated path- and time-integrals, subject to algebraic compatibility of the initial conditions.

math.PR↗

Geometric Ergodicity and Perfect Simulation

This note extends the work of Foss and Tweedie (1997), who showed that availability of the classic Coupling from The Past algorithm of Propp and Wilson (1996) is essentially equivalent to uniform ergodicity for a Markov chain (see also HobertRobert, 2004). In this note we show that all geometrically ergodic chains possess dominated Coupling from The Past algorithms (not necessarily practical!) which are rather closely connected to Foster-Lyapunov criteria.

math.PR↗