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F+Rigging+Spike+%26+Sheath+A200P&create=Create 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In [[theory of probability]], the '''Komlós–Major–Tusnády approximation''' (also known as the '''KMT approximation''', the '''KMT embedding''', or the '''Hungarian embedding''') is an approximation of the [[empirical process]] by a [[Gaussian process]] constructed on the same [[probability space]]. It is named after Hungarian mathematicians [[János Komlós (mathematician)|János Komlós]], [[Gábor Tusnády]], and [[Péter Major]].
 
==Theory==
 
Let <math>U_1,U_2,\ldots</math> be independent [[Uniform distribution (continuous)|uniform]] (0,1) [[random variable]]s. Define a uniform [[empirical distribution function]] as
:<math>F_{U,n}(t)=\frac{1}{n}\sum_{i=1}^n \mathbf{1}_{U_i\leq t},\quad t\in [0,1].</math>
Define a uniform [[empirical process]] as
:<math>\alpha_{U,n}(t)=\sqrt{n}(F_{U,n}(t)-t),\quad t\in [0,1].</math>
The [[Donsker theorem]] (1952) shows that <math>\alpha_{U,n}(t)</math> [[convergence of random variables|converges in law]] to a [[Brownian bridge]] <math>B(t).</math> Komlós, Major and Tusnády established a sharp bound for the speed of this weak convergence.
 
:'''Theorem''' (KMT, 1975) On a suitable [[probability space]] for independent uniform (0,1) r.v. <math>U_1,U_2\ldots</math> the empirical process <math>\{\alpha_{U,n}(t), 0\leq t\leq 1\}</math> can be approximated by a sequence of Brownian bridges <math>\{B_n(t),0\leq t\leq 0\}</math> such that
::<math>P\left\{\sup_{0\leq t\leq 1}|\alpha_{U,n}(t)-B_n(t)|>\frac{1}{\sqrt{n}}(a\log n+x)\right\}\leq b e^{-cx}</math>
:for all positive integers ''n'' and all <math>x>0</math>, where ''a'', ''b'', and ''c'' are positive constants.
 
===Corollary===
A corollary of that theorem is that for any real [[iid]] r.v. <math>X_1,X_2,\ldots,</math> with [[cdf]] <math>F(t),</math> it is possible to construct a probability space where independent{{Clarify|reason=surely alpha and B can't be independent, so what is independent of what?|date=January 2012}} sequences of empirical processes <math>\alpha_{X,n}(t)=\sqrt{n}(F_{X,n}(t)-F(t))</math> and [[Gaussian process]]es <math>G_{F,n}(t)=B_n(F(t))</math> exist such that
: <math>
    \limsup_{n\to\infty} \frac{\sqrt{n}}{\ln n} \big\| \alpha_{X,n} - G_{F,n} \big\|_\infty < \infty,
  </math> &nbsp;&nbsp;&nbsp;&nbsp;[[almost surely]].
 
{{No footnotes|date=November 2010}}
 
==References==
*Komlos, J., Major, P. and Tusnady, G. (1975) An approximation of partial sums of independent rv’s and the sample df. I, ''Wahrsch verw Gebiete/Probability Theory and Related Fields'', 32, 111–131. {{DOI| 10.1007/BF00533093}}
*Komlos, J., Major, P. and Tusnady, G. (1976) An approximation of partial sums of independent rv’s and the sample df. II, ''Wahrsch verw Gebiete/Probability Theory and Related Fields'', 34, 33–58. {{doi|10.1007/BF00532688 }}
 
{{DEFAULTSORT:Komlos-Major-Tusnady Approximation}}
[[Category:Empirical process]]
[[Category:Stochastic processes]]

Revision as of 19:59, 18 January 2014

In theory of probability, the Komlós–Major–Tusnády approximation (also known as the KMT approximation, the KMT embedding, or the Hungarian embedding) is an approximation of the empirical process by a Gaussian process constructed on the same probability space. It is named after Hungarian mathematicians János Komlós, Gábor Tusnády, and Péter Major.

Theory

Let be independent uniform (0,1) random variables. Define a uniform empirical distribution function as

Define a uniform empirical process as

The Donsker theorem (1952) shows that converges in law to a Brownian bridge Komlós, Major and Tusnády established a sharp bound for the speed of this weak convergence.

Theorem (KMT, 1975) On a suitable probability space for independent uniform (0,1) r.v. the empirical process can be approximated by a sequence of Brownian bridges such that
for all positive integers n and all , where a, b, and c are positive constants.

Corollary

A corollary of that theorem is that for any real iid r.v. with cdf it is possible to construct a probability space where independentTemplate:Clarify sequences of empirical processes and Gaussian processes exist such that

    almost surely.

Template:No footnotes

References

  • Komlos, J., Major, P. and Tusnady, G. (1975) An approximation of partial sums of independent rv’s and the sample df. I, Wahrsch verw Gebiete/Probability Theory and Related Fields, 32, 111–131. Electronic Instrument Positions Staff (Standard ) Cameron from Clarence Creek, usually spends time with hobbies and interests which include knotting, property developers in singapore apartment For sale and boomerangs. Has enrolled in a world contiki journey. Is extremely thrilled specifically about visiting .
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