List of Runge–Kutta methods: Difference between revisions

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In [[mathematics]] &mdash; specifically, in [[large deviations theory]] &mdash; the '''tilted large deviation principle''' is a result that allows one to generate a new [[Rate function|large deviation principle]] from an old one by "tilting", i.e. [[Integral|integration]] against an [[Exponential function|exponential]] [[Functional (mathematics)|functional]]. It can be seen as an alternative formulation of [[Varadhan's lemma]].
 
==Statement of the theorem==
 
Let ''X'' be a [[Polish space]] (i.e., a [[separable space|separable]], [[Complete metric space|completely metrizable]] [[topological space]]), and let (''&mu;''<sub>''&epsilon;''</sub>)<sub>''&epsilon;''&gt;0</sub> be a family of [[Probability space|probability measures]] on ''X'' that satisfies the large deviation principle with [[rate function]] ''I''&nbsp;:&nbsp;''X''&nbsp;&rarr;&nbsp;[0,&nbsp;+&infin;].  Let ''F''&nbsp;:&nbsp;''X''&nbsp;&rarr;&nbsp;'''R''' be a [[continuous function]] that is [[bounded function|bounded]] from above.  For each Borel set ''S''&nbsp;&sube;&nbsp;''X'', let
 
:<math>J_{\varepsilon} (S) = \int_{S} e^{- F(x) / \varepsilon} \, \mathrm{d} \mu_{\varepsilon} (x)</math>
 
and define a new family of probability measures (''&nu;''<sub>''&epsilon;''</sub>)<sub>''&epsilon;''&gt;0</sub> on ''X'' by
 
:<math>\nu_{\varepsilon} (S) = \frac{J_{\varepsilon} (S)}{J_{\varepsilon} (X)}.</math>
 
Then (''&nu;''<sub>''&epsilon;''</sub>)<sub>''&epsilon;''&gt;0</sub> satisfies the large deviation principle on ''X'' with rate function ''I''<sup>''F''</sup>&nbsp;:&nbsp;''X''&nbsp;&rarr;&nbsp;[0,&nbsp;+&infin;] given by
 
:<math>I^{F} (x) = \sup_{y \in X} \big[ F(y) - I(y) \big] - \big[ F(x) - I(x) \big].</math>
 
==References==
 
* {{cite book
| last = den Hollander
| first = Frank
| title = Large deviations
| series = [[Fields Institute]] Monographs 14
| publisher = [[American Mathematical Society]]
| location = Providence, RI
| year = 2000
| pages = pp. x+143
| isbn = 0-8218-1989-5
}} {{MathSciNet|id=1739680}}
 
[[Category:Asymptotic analysis]]
[[Category:Mathematical principles]]
[[Category:Probability theorems]]
[[Category:Large deviations theory]]

Revision as of 17:01, 11 November 2013

In mathematics — specifically, in large deviations theory — the tilted large deviation principle is a result that allows one to generate a new large deviation principle from an old one by "tilting", i.e. integration against an exponential functional. It can be seen as an alternative formulation of Varadhan's lemma.

Statement of the theorem

Let X be a Polish space (i.e., a separable, completely metrizable topological space), and let (με)ε>0 be a family of probability measures on X that satisfies the large deviation principle with rate function I : X → [0, +∞]. Let F : X → R be a continuous function that is bounded from above. For each Borel set S ⊆ X, let

Jε(S)=SeF(x)/εdμε(x)

and define a new family of probability measures (νε)ε>0 on X by

νε(S)=Jε(S)Jε(X).

Then (νε)ε>0 satisfies the large deviation principle on X with rate function IF : X → [0, +∞] given by

IF(x)=supyX[F(y)I(y)][F(x)I(x)].

References