Distributions in a sentence

For example, the set of all Gaussian distributions has, nested within it, the set of zero-mean Gaussian distributions: we constrain the mean in the set of all Gaussian distributions to get the zero-mean distributions.

A precise version of this result, given below, holds for distributions of compact support, tempered distributions, and general distributions.

Distributions as derivatives of continuous functions The formal definition of distributions exhibits them as a subspace of a very large space, namely the topological dual of D(U) (or S(R d ) for tempered distributions).

Tempered distributions generalize the bounded (or slow-growing) locally integrable functions; all distributions with compact support and all square-integrable functions are tempered distributions.

The players are very different — Red Hat and a number of Linux distributions and vendors that offer Red Hat Enterprise Linux-compatible distributions — but the question at its core isn’t all that dissimilar from the previous arguments.

For example, the same section of the overhauled tax code that allows distributions to be used for primary and secondary tuition also limits the total amount of distributions to $10,000 per beneficiary per year.

The Trustee generally intends to declare and pay monthly distributions to the extent of forecasted distributions to be received for a calendar quarter from the underlying portfolio, less the estimated operating expenses for the period.

Year-to-date Cumulative Total Return is the percentage change in the Fund's NAV over the year-to-date time period including distributions paid and assuming reinvestment of those distributions.

A limitation of the theory of distributions (and hyperfunctions) is that there is no associative product of two distributions extending the product of a distribution by a smooth function, as has been proved by Laurent Schwartz in the 1950s.

An example of such distributions could be a mix of discrete and continuous distributions—for example, a random variable that is 0 with probability 1/2, and takes a random value from a normal distribution with probability 1/2.

As a different example, the set of positive-mean Gaussian distributions, which has dimension 2, is nested within the set of all Gaussian distributions.

Common probability distributions main The following is a list of some of the most common probability distributions, grouped by the type of process that they are related to.

Distributions main Under some circumstances, it is possible to define the convolution of a function with a distribution, or of two distributions.

Early Linux distributions were installed using sets of floppies but this has been abandoned by all major distributions.

Further, in multimodal distributions and discrete distributions, skewness is also difficult to interpret.

If a theorem can be proved in this general setting, it holds for both discrete and continuous distributions as well as others; separate proofs are not required for discrete and continuous distributions.

In each case, the distributions considered under the null hypothesis are continuous distributions but are otherwise unrestricted.

Likelihoods for mixed continuous discrete distributions The above can be extended in a simple way to allow consideration of distributions which contain both discrete and continuous components.

Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known.

Operations on distributions Many operations which are defined on smooth functions with compact support can also be defined for distributions.