Examples of using Random variables in English and their translations into Russian
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Log-normal distributions are encountered in many fields, wherever a variable is formed as the product of many independent positive random variables, for example in the study of turbulence.
Hoeffding's inequality can be applied to the important special case of identically distributed Bernoulli random variables, and this is how the inequality is often used in combinatorics and computer science.
It is assumed throughout the thesis that various activities durations are mutually independent random variables kXXX,,, 21.
second maximum, random variables, sorting arrays,
extreme-value distributed random variables.
In mathematics, the values of analyzed body parameters can be considered as random variables RV.
the difference of two independent random variables.
We describe probability measures on the two dimensional torus which are characterized by the independence of linear forms from two independent random variables.
sampling with replacement where ordering matters is comparable to describing the joint distribution of N separate random variables, each with an X-fold categorical distribution.
as kernel density estimates converge faster to the true underlying density for continuous random variables.
The use of a family of mixtureû of shifted distributions for the modeling of perforated distributions and random variables has been justified.
The odds ratio can also be defined in terms of the joint probability distribution of two binary random variables.
HSIC always takes a non-negative value, and is zero if and only if two random variables are statistically independent when a universal reproducing kernel such as the Gaussian kernel is used.
The negentropy method are based on an important property of Gaussian distribution: a Gaussian variable has the largest entropy among all continuous random variables of equal variance.
Any collection of mutually independent random variables is pairwise independent,
formally known as IEEE 1800-2005 SystemVerilog, introduces many new features(classes, random variables, and properties/assertions) to address the growing need for better test bench randomization,
Obviously, the above mentioned approaches to the problem of diagnosing a disease using statistical functionals based on blood analyzes and considered random variables, are not the only possible methodology.
maximizes the expectation of some function of the decisions and the random variables.
The distribution is also applicable to a special case of the difference of dependent Poisson random variables, but just the obvious case where the two variables have a common additive random contribution which is cancelled by the differencing:
It is also a product distribution: it is the distribution of the product of two independent random variables, one having a gamma distribution with mean 1 and shape parameter L{\displaystyle L},