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Applications and the study of phenomena have in turn inspired the proposal of new stochastic processes. Examples of such stochastic processes include the Wiener process or Brownian motion process, [a] used by Louis Bachelier to study price changes on the Paris Bourse, [21] and the Poisson process, used by A. K. Erlang to study the number of ...
Stochastic music was pioneered by Iannis Xenakis, who coined the term stochastic music. Specific examples of mathematics, statistics, and physics applied to music composition are the use of the statistical mechanics of gases in Pithoprakta, statistical distribution of points on a plane in Diamorphoses, minimal constraints in Achorripsis, the ...
Developmental noise or stochastic noise is a concept within developmental biology in which the observable characteristics or traits varies between individuals even though both individuals share the same genetic code and the other environmental factors are completely the same.
This list is currently incomplete. See also Category:Stochastic processes. Basic affine jump diffusion; Bernoulli process: discrete-time processes with two possible states. Bernoulli schemes: discrete-time processes with N possible states; every stationary process in N outcomes is a Bernoulli scheme, and vice versa. Bessel process; Birth ...
This list of research methods in biology is an index to articles about research methodologies used in various branches ... Stochastic process that describes finite ...
A canonical model for stochastic gene expression, known as the two-state or telegraph [30] model. DNA flips between "inactive" and "active" states (involving, for example, chromatin remodelling and transcription factor binding). Active DNA is transcribed to produce mRNA which is translated to produce protein, both of which are degraded.
The most common formulation of a branching process is that of the Galton–Watson process.Let Z n denote the state in period n (often interpreted as the size of generation n), and let X n,i be a random variable denoting the number of direct successors of member i in period n, where X n,i are independent and identically distributed random variables over all n ∈{ 0, 1, 2, ...} and i ∈ {1 ...
A Moran process or Moran model is a simple stochastic process used in biology to describe finite populations. The process is named after Patrick Moran, who first proposed the model in 1958. [1] It can be used to model variety-increasing processes such as mutation as well as variety-reducing effects such as genetic drift and natural selection.