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In [[mathematics]], the '''Paley–Zygmund inequality''' bounds the | |||
probability that a positive random variable is small, in terms of | |||
its [[expected value|mean]] and [[variance]] (i.e., its first two [[moment (mathematics)|moments]]). The inequality was | |||
proved by [[Raymond Paley]] and [[Antoni Zygmund]]. | |||
'''Theorem''': If ''Z'' ≥ 0 is a [[random variable]] with | |||
finite variance, and if 0 < ''θ'' < 1, then | |||
:<math> | |||
\operatorname{P}( Z \ge \theta\operatorname{E}[Z] ) | |||
\ge (1-\theta)^2 \frac{\operatorname{E}[Z]^2}{\operatorname{E}[Z^2]}. | |||
</math> | |||
'''Proof''': First, | |||
:<math> | |||
\operatorname{E}[Z] = \operatorname{E}[ Z \, \mathbf{1}_{\{ Z < \theta \operatorname{E}[Z] \}}] + \operatorname{E}[ Z \, \mathbf{1}_{\{ Z \ge \theta \operatorname{E}[Z] \}} ]. | |||
</math> | |||
The first addend is at most <math>\theta \operatorname{E}[Z]</math>, while the second is at most <math> \operatorname{E}[Z^2]^{1/2} \operatorname{P}( Z \ge \theta\operatorname{E}[Z])^{1/2} </math> by the [[Cauchy–Schwarz inequality]]. The desired inequality then follows. ∎ | |||
== Related inequalities == | |||
The Paley–Zygmund inequality can be written as | |||
:<math> | |||
\operatorname{P}( Z \ge \theta \operatorname{E}[Z] ) | |||
\ge \frac{(1-\theta)^2 \, \operatorname{E}[Z]^2}{\operatorname{var} Z + \operatorname{E}[Z]^2}. | |||
</math> | |||
This can be improved. By the [[Cauchy–Schwarz inequality]], | |||
:<math> | |||
\operatorname{E}[Z - \theta \operatorname{E}[Z]] | |||
\le \operatorname{E}[ (Z - \theta \operatorname{E}[Z]) \mathbf{1}_{\{ Z \ge \theta \operatorname{E}[Z] \}} ] | |||
\le \operatorname{E}[ (Z - \theta \operatorname{E}[Z])^2 ]^{1/2} \operatorname{P}( Z \ge \theta \operatorname{E}[Z] )^{1/2} | |||
</math> | |||
which, after rearranging, implies that | |||
:<math> | |||
\operatorname{P}(Z \ge \theta \operatorname{E}[Z]) | |||
\ge \frac{(1-\theta)^2 \operatorname{E}[Z]^2}{\operatorname{E}[( Z - \theta \operatorname{E}[Z] )^2]} | |||
= \frac{(1-\theta)^2 \operatorname{E}[Z]^2}{\operatorname{var} Z + (1-\theta)^2 \operatorname{E}[Z]^2}. | |||
</math> | |||
This inequality is sharp; equality is achieved if Z almost surely equals a positive constant, for example. | |||
== References== | |||
* R.E.A.C.Paley and A.Zygmund, ''A note on analytic functions in the unit circle'', Proc. Camb. Phil. Soc. 28, 1932, 266–272 | |||
{{DEFAULTSORT:Paley-Zygmund inequality}} | |||
[[Category:Probabilistic inequalities]] |
Revision as of 06:08, 22 January 2014
In mathematics, the Paley–Zygmund inequality bounds the probability that a positive random variable is small, in terms of its mean and variance (i.e., its first two moments). The inequality was proved by Raymond Paley and Antoni Zygmund.
Theorem: If Z ≥ 0 is a random variable with finite variance, and if 0 < θ < 1, then
Proof: First,
The first addend is at most , while the second is at most by the Cauchy–Schwarz inequality. The desired inequality then follows. ∎
Related inequalities
The Paley–Zygmund inequality can be written as
This can be improved. By the Cauchy–Schwarz inequality,
which, after rearranging, implies that
This inequality is sharp; equality is achieved if Z almost surely equals a positive constant, for example.
References
- R.E.A.C.Paley and A.Zygmund, A note on analytic functions in the unit circle, Proc. Camb. Phil. Soc. 28, 1932, 266–272