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In computer science, quickselect is a selection algorithm to find the kth smallest element in an unordered list, also known as the kth order statistic.Like the related quicksort sorting algorithm, it was developed by Tony Hoare, and thus is also known as Hoare's selection algorithm. [1]
A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which returns successive integers:
The Dirac comb of period 2 π, although not strictly a function, is a limiting form of many directional distributions. It is essentially a wrapped Dirac delta function. It represents a discrete probability distribution concentrated at 2 π n — a degenerate distribution — but the notation treats it as if it were a continuous distribution.
On Wikipedia and other sites running on MediaWiki, Special:Random can be used to access a random article in the main namespace; this feature is useful as a tool to generate a random article. Depending on your browser, it's also possible to load a random page using a keyboard shortcut (in Firefox , Edge , and Chrome Alt-Shift + X ).
The example includes link to a matrix diagram that illustrates how Fisher-Yates is unbiased while the naïve method (select naïve swap i -> random) is biased. Select Fisher-Yates and change the line to have pre-decrement --m rather than post-decrement m--giving i = Math.floor(Math.random() * --m);, and you get Sattolo's algorithm where no item ...
In some cases, data reveals an obvious non-random pattern, as with so-called "runs in the data" (such as expecting random 0–9 but finding "4 3 2 1 0 4 3 2 1..." and rarely going above 4). If a selected set of data fails the tests, then parameters can be changed or other randomized data can be used which does pass the tests for randomness.
If we associate with each item of the input a uniformly generated random number, the k items with the largest (or, equivalently, smallest) associated values form a simple random sample. [3] A simple reservoir-sampling thus maintains the k items with the currently largest associated values in a priority queue .