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Berry-Esseen bounds for combinatorial central limit theorems and pattern occurrences, using zero and size biasing. (English) Zbl 1087.60021
Author develops Berry-Esseen type bounds for normal approximation, based on zero-couplings and size-bias couplings. Stein’s method, which characterizes equations to obtain bounds on the error when approximating distrubutions by a given target, is used to obtain that bound. The results are applied to bound the proximity to the normal in combinatorial central limit theorems in which the random permutation has either a uniform distribution or one that is constant over permutations with the same cycle type, with no fixed points; to counting the number of occurrences of fixed, relatively ordered subsequences, such as rising sequences, in a random permutation; and to counting the number of occurrences of patterns, local extremes, and subgraphs in finite graphs. From a characterizing equation a difference or differential equation can be set up to bound the difference between the exepctation of a test function $$h$$ when evaluated on a given variable $$Y$$ and then on the variable $$X$$ having the target distribution. For the normal, with $$X$$ having the same mean $$\mu$$ and variance $$\sigma^2$$ as $$Y$$, the characterizing equation leads to the differential equation
$h((y-\mu)/\sigma) - Nh = \sigma^2 f'(y) - (y-\mu)f(y),$
where $$Nh = Eh(Z)$$ with $$Z\sim N(0,1)$$, the standard normal mean of the test function $$h.$$ Tow concepts of couplings of a given $$Y$$ are introduced to achieve normal bounds. With $$W=(Y-\mu)/\sigma$$, many authors have been successful in obtaining bounds on the distance
$\delta = \sup_{h\in H} | Eh(W)-Nh |$
to the normal, over classes of nonsmooth functions $$H$$, using Stein’s method. The author takes the smoothing inequality approach. In Theorem 1.1, for the case of the first type of couplings, the bound on $$\delta$$ is obtained. In Section 2, the result in Theorem 1.1 is applied to random variables of the form $$Y=\sum^{n}_{i=1} a_{i, \pi(i)},$$ depending on a fixed array of real numbers $$\{a_{ij}\}^{n}_{i,j=1}$$ and a random permutation $$\pi\in S_n$$, the symmetric group of order $$n$$. In Section 2.1 the author considers $$\pi$$ to have the uniform distribution on $$S_n$$ and, in Section 2.2, he considers distributions constant with respect to cycle type, with no fixed points. For a case of the second size-bias coupling, the author presents Theorem 1.2, which gives a bound on $$\delta$$ that depends on the size of the absolute value of difference between couplings. In Section 3, the author drives corollaries to Theorem 1.2 to obtain Berry-Esseen bounds for the number of occurrences of fixed, relatively ordered subsequences, such as rising sequences, in a radom permutation, and of color patterns, local maxima, and subgraphs in finite graphs. Several examples are given in two sections.

##### MSC:
 60F05 Central limit and other weak theorems 60C05 Combinatorial probability
##### Keywords:
Smoothing inequality; Stein’s method; permutation; graph
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##### References:
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