Marcinkiewicz–Zygmund Inequality
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In
mathematics Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many ar ...
, the Marcinkiewicz–Zygmund inequality, named after
Józef Marcinkiewicz Józef Marcinkiewicz (; 30 March 1910 in Cimoszka, near Białystok, Poland – 1940 in Kharkiv, USSR) was a Polish mathematician. Life and career He was a student of Antoni Zygmund; and later worked with Juliusz Schauder, Stefan Kaczmarz ...
and
Antoni Zygmund Antoni Zygmund (December 26, 1900 – May 30, 1992) was a Polish-American mathematician. He worked mostly in the area of mathematical analysis, including harmonic analysis, and he is considered one of the greatest analysts of the 20th century. ...
, gives relations between moments of a collection of
independent random variables Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically independent, or stochastically independent if, informally speaking, the occurrence of ...
. It is a generalization of the rule for the sum of
variance In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation (SD) is obtained as the square root of the variance. Variance is a measure of dispersion ...
s of independent random variables to moments of arbitrary order. It is a special case of the Burkholder-Davis-Gundy inequality in the case of discrete-time martingales.


Statement of the inequality

Theorem J. Marcinkiewicz and A. Zygmund. Sur les fonctions indépendantes. ''Fund. Math.'', 28:60–90, 1937. Reprinted in Józef Marcinkiewicz, ''Collected papers'', edited by Antoni Zygmund, Panstwowe Wydawnictwo Naukowe, Warsaw, 1964, pp. 233–259. Yuan Shih Chow and Henry Teicher. ''Probability theory. Independence, interchangeability, martingales''. Springer-Verlag, New York, second edition, 1988. If \textstyle X_, \textstyle i=1,\ldots,n, are independent random variables such that \textstyle E\left( X_\right) =0 and \textstyle E\left( \left\vert X_\right\vert ^\right) <+\infty, \textstyle 1\leq p<+\infty, then : A_E\left( \left( \sum_^\left\vert X_\right\vert ^\right) _^\right) \leq E\left( \left\vert \sum_^X_\right\vert ^\right) \leq B_E\left( \left( \sum_^\left\vert X_\right\vert ^\right) _^\right) where \textstyle A_ and \textstyle B_ are positive constants, which depend only on \textstyle p and not on the underlying distribution of the random variables involved.


The second-order case

In the case \textstyle p=2, the inequality holds with \textstyle A_=B_=1, and it reduces to the rule for the sum of variances of independent random variables with zero mean, known from elementary statistics: If \textstyle E\left( X_\right) =0 and \textstyle E\left( \left\vert X_\right\vert ^\right) <+\infty, then : \mathrm\left(\sum_^X_\right)=E\left( \left\vert \sum_^X_\right\vert ^\right) =\sum_^\sum_^E\left( X_\overline_\right) =\sum_^E\left( \left\vert X_\right\vert ^\right) =\sum_^\mathrm\left(X_\right).


See also

Several similar moment inequalities are known as
Khintchine inequality The Khintchine inequality, is a result in probability also frequently used in mathematical analysis, analysis bounding the expectation a weighted sum of Rademacher distribution , Rademacher random variables with Sequence_space#ℓp_spaces , squa ...
and Rosenthal inequalities, and there are also extensions to more general symmetric
statistic A statistic (singular) or sample statistic is any quantity computed from values in a sample which is considered for a statistical purpose. Statistical purposes include estimating a population parameter, describing a sample, or evaluating a hypot ...
s of independent random variables.R. Ibragimov and Sh. Sharakhmetov. Analogues of Khintchine, Marcinkiewicz–Zygmund and Rosenthal inequalities for symmetric statistics. ''Scandinavian Journal of Statistics'', 26(4):621–633, 1999.


Notes

{{DEFAULTSORT:Marcinkiewicz-Zygmund inequality Statistical inequalities Probabilistic inequalities Theorems in probability theory Theorems in functional analysis