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Random graphs may be described simply by a probability distribution, or by a random process which generates them. [1] [2] The theory of random graphs lies at the intersection between graph theory and probability theory. From a mathematical perspective, random graphs are used to answer questions about the properties of typical graphs.
[1] [2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [ 3 ] For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads , and ...
This does not look random, but it satisfies the definition of random variable. This is useful because it puts deterministic variables and random variables in the same formalism. The discrete uniform distribution, where all elements of a finite set are equally likely. This is the theoretical distribution model for a balanced coin, an unbiased ...
A random r-regular graph is a graph selected from ,, which denotes the probability space of all r-regular graphs on vertices, where < and is even. [1] It is therefore a particular kind of random graph, but the regularity restriction significantly alters the properties that will hold, since most graphs are not regular.
Pages in category "Random graphs" The following 24 pages are in this category, out of 24 total. ... Statistics; Cookie statement; Mobile view ...
A random sample can be thought of as a set of objects that are chosen randomly. More formally, it is "a sequence of independent, identically distributed (IID) random data points." In other words, the terms random sample and IID are synonymous. In statistics, "random sample" is the typical terminology, but in probability, it is more common to ...
In practical applications, the domain over which the function is defined is a time interval (time series) or a region of space (random field). Familiar examples of time series include stock market and exchange rate fluctuations, signals such as speech, audio and video; medical data such as a patient's EKG, EEG, blood pressure or temperature ...
There are two closely related variants of the Erdős–Rényi random graph model. A graph generated by the binomial model of Erdős and Rényi (p = 0.01) In the (,) model, a graph is chosen uniformly at random from the collection of all graphs which have nodes and edges. The nodes are considered to be labeled, meaning that graphs obtained from ...