The Annals of Applied Probability

Matching Random Samples in Many Dimensions

Michel Talagrand

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Abstract

Consider any norm $N$ on $\mathbb{R}^d, d \geq 3$, and independent uniformly distributed points $X_1, \ldots, X_n, \ldots; Y_1, \ldots, Y_n, \ldots$ in $\lbrack 0, 1\rbrack^d$. Consider the random variable $M_n = \inf \sum_{i \leq n} N(X_i - Y_{\sigma(i)})$, where the infimum is taken over all permutations $\sigma$ of $\{1, \ldots, n\}$. We show that for some universal constant $K$, we have $\lim \sup_{n \rightarrow \infty} M_n n^{-1 + 1/d} \leq r_N \big(1 + K \frac{\log d}{d}\big)mathrm{a,s.},$ where $r_N$ is the radius of the ball for $N$ of volume 1.

Article information

Source
Ann. Appl. Probab., Volume 2, Number 4 (1992), 846-856.

Dates
First available in Project Euclid: 19 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1177005578

Digital Object Identifier
doi:10.1214/aoap/1177005578

Mathematical Reviews number (MathSciNet)
MR1189420

Zentralblatt MATH identifier
0761.60007

JSTOR
links.jstor.org

Subjects
Primary: 60C05: Combinatorial probability
Secondary: 05C70: Factorization, matching, partitioning, covering and packing

Keywords
Matchings transportation cost empirical measure

Citation

Talagrand, Michel. Matching Random Samples in Many Dimensions. Ann. Appl. Probab. 2 (1992), no. 4, 846--856. doi:10.1214/aoap/1177005578. https://projecteuclid.org/euclid.aoap/1177005578


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