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This function is fitted to the distribution of detection ranges represented as a probability density function (PDF). The PDF is a histogram of collected distances and describes the probability that an object at distance y will be detected by an observer on the center line, with detections on the line itself (y = 0) assumed to be certain (P = 1).
In statistics, probability density estimation or simply density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to which a large population is distributed; the data are usually thought of as ...
The majority problem, or density classification task, is the problem of finding one-dimensional cellular automaton rules that accurately perform majority voting.. Using local transition rules, cells cannot know the total count of all the ones in system.
The density of states related to volume V and N countable energy levels is defined as: = = (()). Because the smallest allowed change of momentum for a particle in a box of dimension and length is () = (/), the volume-related density of states for continuous energy levels is obtained in the limit as ():= (()), Here, is the spatial dimension of the considered system and the wave vector.
Hydrostatic weighing, also referred to as underwater weighing, hydrostatic body composition analysis and hydrodensitometry, is a technique for measuring the density of a living person's body. It is a direct application of Archimedes' principle , that an object displaces its own volume of water.
The objective of the densest at most problem is to find the maximum density subgraph on at most vertices. Andersen and Chellapilla showed that if there exists an α {\displaystyle \alpha } -approximation for this problem then that will lead to an Θ ( α 2 ) {\displaystyle \Theta (\alpha ^{2})} -approximation for the densest k {\displaystyle k ...
Marginal probability density function [ edit ] Given two continuous random variables X and Y whose joint distribution is known, then the marginal probability density function can be obtained by integrating the joint probability distribution, f , over Y, and vice versa.
calculation of () Radial distribution function for the Lennard-Jones model fluid at =, =.. In statistical mechanics, the radial distribution function, (or pair correlation function) () in a system of particles (atoms, molecules, colloids, etc.), describes how density varies as a function of distance from a reference particle.
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