Multivariate concentration of measure type results using exchangeable pairs and size biasing

preprint2010arXivOpen access

Abstract

Let (W,W′)(\mathbf{W,W'}) be an exchangeable pair of vectors in Rk\mathbb{R}^k. Suppose this pair satisfies \beas E(\mathbf{W}'|\mathbf{W})=(I_k-Λ)\mathbf{W}+\mathbf{R(W)}. \enas If ∣∣W−W′∣∣2≤K||\mathbf{W-W'}||_2\le K and R(W)=0\mathbf{R(W)}=0, then concentration of measure results of following form is proved for all w⪰0\mathbf{w}\succeq 0 when the moment generating function of W\mathbf{W} is finite. \beas P(\mathbf{W}\succeq\mathbf{w}),P(\mathbf{W}\preceq -\mathbf{w})\le \exp(-\frac{||\mathbf{w}||_2^2}{2K^2ν_1}), \enas for an explicit constant ν1ν_1, where ⪰\succeq stands for coordinate wise ≥\ge ordering. This result is applied to examples like complete non degenerate U-statistics. Also, we deal with the example of doubly indexed permutation statistics where R(W)≠0\mathbf{R(W)}\neq 0 and obtain similar concentration of measure inequalities. Practical examples from doubly indexed permutation statistics include Mann-Whitney-Wilcoxon statistic and random intersection of two graphs. Both these two examples are used in nonparametric statistical testing. We conclude the paper with a multivariate generalization of a recent concentration result due to Ghosh and Goldstein \cite{cnm} involving bounded size bias couplings.

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