Normal Approximation for Coverage Models over Binomial Point Processes by Larry Goldstein

نویسنده

  • MATHEW D. PENROSE
چکیده

We give error bounds which demonstrate optimal rates of convergence in the CLT for the total covered volume and the number of isolated shapes, for germ-grain models with fixed grain radius over a binomial point process of n points in a toroidal spatial region of volume n. The proof is based on Stein's method via size-biased couplings. 1. Introduction. Given a collection of n independent uniformly distributed random points in a d-dimensional cube of volume n (the so-called binomial point process), let V denote the (random) total volume of the union of interpenetrating balls of fixed radius ρ centered at these points, and let S denote the number of balls of radius ρ/2 (centered at the same set of points) which are singletons, that is, do not overlap any other such ball. These variables are fundamental topics of interest in the stochastic geometry of coverage processes and random geometric graphs [9, 10, 13, 18]. As n → ∞ with ρ fixed (the so-called thermodynamic limit), both V and S are known to satisfy a central limit theorem (CLT) [12, 13, 16]. In the present work we provide associated Berry–Esseen type results; that is, we show under periodic boundary conditions that the cumulative distribution functions converge to that of the normal at the same O(n −1/2) rate as for a sum of n independent identically distributed variables, and provide bounds on the quality of the normal approximation for finite n. Were we to consider instead a Poisson-distributed number of points, that is, a Poisson point process instead of a binomial one, both of our variables of interest could be expressed as sums of locally dependent random variables, and thereby Berry–Esseen type bounds could be (and have been) obtained by known methods [1, 8, 15, 17]. But with a nonrandom number of points, the local dependence is lost and the de-Poissonization arguments in [13, 16] do not provide error bounds for the de-Poissonized CLTs. The early work of Moran [11, 12] on V was in response to queries in the statistical physics literature (including the well-known

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Normal approximation for coverage models over binomial point processes

We give error bounds which demonstrate optimal rates of convergence in the CLT for the total covered volume and the number of isolated shapes, for germ-grain models with fixed grain radius over a binomial point process of n points in a toroidal spatial region of volume n. The proof is based on Stein’s method via size-biased couplings. 1 Department of Mathematics, University of Southern Californ...

متن کامل

Clubbed Binomial Approximation for the Lightbulb Process

In the so called lightbulb process, on days r = 1, . . . ,n, out of n lightbulbs, all initially off, exactly r bulbs selected uniformly and independent of the past have their status changed from off to on, or vice versa. With Wn the number of bulbs on at the terminal time n and Cn a suitable clubbed binomial distribution, dTV(Wn,Cn)≤ 2.7314 √ ne−(n+1)/3 for all n≥ 1. The result is shown using S...

متن کامل

Larry Goldstein – Yosef Rinott

We consider a permutation method for testing whether observations given in their natural pairing exhibit an unusual level of similarity in situations where any two observations may be similar at some unknown baseline level. Under a null hypotheses where there is no distinguished pairing of the observations, a normal approximation with explicit bounds and rates is presented for determining appro...

متن کامل

Growth Estimators and Confidence Intervals for the Mean of Negative Binomial Random Variables with Unknown Dispersion

The negative binomial distribution becomes highly skewed under extreme dispersion. Even at moderately large sample sizes, the sample mean exhibits a heavy right tail. The standard normal approximation often does not provide adequate inferences about the data’s expected value in this setting. In previous work, we have examined alternative methods of generating confidence intervals for the expect...

متن کامل

Zero Biasing in One and Higher Dimensions, and Applications

Given any mean zero, finite variance σ2 random variable W , there exists a unique distribution on a variable W ∗ such that EWf(W ) = σ2Ef ′(W ∗) for all absolutely continuous functions f for which these expectations exist. This distributional ‘zero bias’ transformation of W to W ∗, of which the normal is the unique fixed point, was introduced in [9] to obtain bounds in normal approximations. Af...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008