Box–Muller Transform

picture info	Box–Muller Transform The Box–Muller transform, by George Edward Pelham Box and Mervin Edgar Muller, is a random number sampling method for generating pairs of independent, standard, normally distributed (zero expectation, unit variance) random numbers, given a source of uniformly distributed random numbers. The method was first mentioned explicitly by Raymond E. A. C. Paley and Norbert Wiener in their 1934 treatise on Fourier transforms in the complex domain. Given the status of these latter authors and the widespread availability and use of their treatise, it is almost certain that Box and Muller were well aware of its contents. The Box–Muller transform is commonly expressed in two forms. The basic form as given by Box and Muller takes two samples from the uniform distribution on the interval and maps them to two standard, normally distributed samples. The polar form takes two samples from a different interval, , and maps them to two normally distributed samples without the use of sine or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Bivariate Normal In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be ''k''-variate normally distributed if every linear combination of its ''k'' components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables, each of which clusters around a mean value. Definitions Notation and parametrization The multivariate normal distribution of a ''k''-dimensional random vector \mathbf = (X_1,\ldots,X_k)^ can be written in the following notation: : \mathbf\ \sim\ \mathcal(\boldsymbol\mu,\, \boldsymbol\Sigma), or to make it explicitly known that \mathbf i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Transforms Transform may refer to: Arts and entertainment Transform (scratch), a type of scratch used by turntablists ''Transform'' (Alva Noto album), 2001 * ''Transform'' (Howard Jones album) or the title song, 2019 * ''Transform'' (Powerman 5000 album) or the title song, 2003 * ''Transform'' (Rebecca St. James album), 2000 * ''Transform'' (single album), by Teen Top, or the title song, 2011 "Transform", a song by Daniel Caesar from ''Freudian'', 2017 "Transform", a song by Your Memorial from ''Redirect'', 2012 Mathematics, science, and technology Mathematics Transformation (function), concerning functions from sets to themselves Transform theory, theory of integral transforms List of transforms, a list of mathematical transforms Integral transform, a type of mathematical transform Computer graphics Transform coding, a type of data compression for digital images Transform, clipping, and lighting, a term used in computer graphics Other sciences Transformation (genetics), the ... [...More Info...] [...Related Items...] OR:* [Wikipedia] [Google] [Baidu]
	Marsaglia Polar Method The Marsaglia polar method is a pseudo-random number sampling method for generating a pair of independent standard normal random variables. Standard normal random variables are frequently used in computer science, computational statistics, and in particular, in applications of the Monte Carlo method. The polar method works by choosing random points (''x'', ''y'') in the square −1 < ''x'' < 1, −1 < ''y'' < 1 until : $0 < s=x^2+y^2 < 1, \,$ and then returning the required pair of normal random variable s as : $x\sqrt\,,\ \ y\sqrt,$ or, equivalently, : $\frac \sqrt\,,\ \ \frac \sqrt,$ where $x/\sqrt$ and $y/\sqrt$ represent the cosine ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	Inverse Transform Sampling Inverse transform sampling (also known as inversion sampling, the inverse probability integral transform, the inverse transformation method, or the Smirnov transform) is a basic method for pseudo-random number sampling, i.e., for generating sample numbers at random from any probability distribution given its cumulative distribution function. Inverse transformation sampling takes uniform samples of a number u between 0 and 1, interpreted as a probability, and then returns the smallest number x\in\mathbb R such that F(x)\ge u for the cumulative distribution function F of a random variable. For example, imagine that F is the standard normal distribution with mean zero and standard deviation one. The table below shows samples taken from the uniform distribution and their representation on the standard normal distribution. We are randomly choosing a proportion of the area under the curve and returning the number in the domain such that exactly this proportion of the area occurs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Random Seed A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers. For a seed to be used in a pseudorandom number generator, it does not need to be random. Because of the nature of number generating algorithms, so long as the original seed is ignored, the rest of the values that the algorithm generates will follow probability distribution in a pseudorandom manner. However, a non-random seed will be cryptographically insecure, as it can allow an adversary to predict the pseudorandom numbers generated. The choice of a good random seed is crucial in the field of computer security. When a secret encryption key is pseudorandomly generated, having the seed will allow one to obtain the key. High entropy is importan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Standard Normal Deviate Standard may refer to: Symbols * Colours, standards and guidons, kinds of military signs * Standard (emblem), a type of a large symbol or emblem used for identification Norms, conventions or requirements * Standard (metrology), an object that bears a defined relationship to a unit of measure used for calibration of measuring devices * Standard (timber unit), an obsolete measure of timber used in trade * Breed standard (also called bench standard), in animal fancy and animal husbandry * BioCompute Standard, a standard for next generation sequencing * ''De facto'' standard, product or system with market dominance * Gold standard, a monetary system based on gold; also used metaphorically for the best of several options, against which the others are measured * Internet Standard, a specification ratified as an open standard by the Internet Engineering Task Force * Learning standards, standards applied to education content * Standard displacement, a naval term describing the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Intrinsic Function In computer software, in compiler theory, an intrinsic function, also called built-in function or builtin function, is a function ( subroutine) available for use in a given programming language whose implementation is handled specially by the compiler. Typically, it may substitute a sequence of automatically generated instructions for the original function call, similar to an inline function. Unlike an inline function, the compiler has an intimate knowledge of an intrinsic function and can thus better integrate and optimize it for a given situation. Compilers that implement intrinsic functions may enable them only when a program requests optimization, otherwise falling back to a default implementation provided by the language runtime system (environment). Vectorization and parallelization Intrinsic functions are often used to explicitly implement vectorization and parallelization in languages which do not address such constructs. Some application programming interfaces (API ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Rejection Sampling In numerical analysis and computational statistics, rejection sampling is a basic technique used to generate observations from a distribution. It is also commonly called the acceptance-rejection method or "accept-reject algorithm" and is a type of exact simulation method. The method works for any distribution in \mathbb^m with a density. Rejection sampling is based on the observation that to sample a random variable in one dimension, one can perform a uniformly random sampling of the two-dimensional Cartesian graph, and keep the samples in the region under the graph of its density function. Note that this property can be extended to ''N''-dimension functions. Description To visualize the motivation behind rejection sampling, imagine graphing the probability density function (PDF) of a random variable onto a large rectangular board and throwing darts at it. Assume that the darts are uniformly distributed around the board. Now remove all of the darts that are outside the area und ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
picture info	The Art Of Computer Programming ''The Art of Computer Programming'' (''TAOCP'') is a comprehensive multi-volume monograph written by the computer scientist Donald Knuth presenting programming algorithms and their analysis. it consists of published volumes 1, 2, 3, 4A, and 4B, with more expected to be released in the future. The Volumes 1–5 are intended to represent the central core of computer programming for sequential machines; the subjects of Volumes 6 and 7 are important but more specialized. When Knuth began the project in 1962, he originally conceived of it as a single book with twelve chapters. The first three volumes of what was then expected to be a seven-volume set were published in 1968, 1969, and 1973. Work began in earnest on Volume 4 in 1973, but was suspended in 1977 for work on typesetting prompted by the second edition of Volume 2. Writing of the final copy of Volume 4A began in longhand in 2001, and the first online pre-fascicle, 2A, appeared later in 2001. The first published installment ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]
	Numerical Recipes ''Numerical Recipes'' is the generic title of a series of books on algorithm In mathematics and computer science, an algorithm () is a finite sequence of Rigour#Mathematics, mathematically rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algo ...s and numerical analysis by William H. Press, Saul A. Teukolsky, William T. Vetterling and Brian P. Flannery. In various editions, the books have been in print since 1986. The most recent edition was published in 2007. Overview The ''Numerical Recipes'' books cover a range of topics that include both classical numerical analysis (interpolation, Numerical integration, integration, linear algebra, differential equations, and so on), signal processing (Fast Fourier transform, Fourier methods, Digital filter, filtering), statistical treatment of data, and a few topics in machine learning (hidden Markov model, support vector machines). The writing style is acc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu]