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Multivariate Continuous Distributions
Multivariate is the quality of having multiple variables. It may also refer to: In mathematics * Multivariable calculus * Multivariate function * Multivariate polynomial * Multivariate interpolation * Multivariate optimization In computing * Multivariate cryptography * Multivariate division algorithm * Multivariate optical computing In statistics * Multivariate analysis * Multivariate random variable * Multivariate regression * Multivariate statistics See also * Univariate In mathematics, a univariate object is an expression (mathematics), expression, equation, function (mathematics), function or polynomial involving only one Variable (mathematics), variable. Objects involving more than one variable are ''wikt:multi ... * Bivariate (other) {{disambiguation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate (mathematics)
In mathematics, a univariate object is an expression (mathematics), expression, equation, function (mathematics), function or polynomial involving only one Variable (mathematics), variable. Objects involving more than one variable are ''wikt:multivariate, multivariate''. In some cases the distinction between the univariate and multivariate cases is fundamental; for example, the fundamental theorem of algebra and Euclid's algorithm for polynomials are fundamental properties of univariate polynomials that cannot be generalized to multivariate polynomials. In statistics, a univariate Frequency distribution, distribution characterizes one variable, although it can be applied in other ways as well. For example, univariate data are composed of a single scalar (mathematics), scalar component. In time series analysis, the whole time series is the "variable": a univariate time series is the series of values over time of a single quantity. Correspondingly, a "multivariate time series" charac ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariable Calculus
Multivariable calculus (also known as multivariate calculus) is the extension of calculus in one variable to calculus with functions of several variables: the differentiation and integration of functions involving multiple variables ('' multivariate''), rather than just one. Multivariable calculus may be thought of as an elementary part of calculus on Euclidean space. The special case of calculus in three dimensional space is often called ''vector calculus''. Introduction In single-variable calculus, operations like differentiation and integration are made to functions of a single variable. In multivariate calculus, it is required to generalize these to multiple variables, and the domain is therefore multi-dimensional. Care is therefore required in these generalizations, because of two key differences between 1D and higher dimensional spaces: # There are infinite ways to approach a single point in higher dimensions, as opposed to two (from the positive and negative direct ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Function
In mathematics, a function from a set to a set assigns to each element of exactly one element of .; the words ''map'', ''mapping'', ''transformation'', ''correspondence'', and ''operator'' are sometimes used synonymously. The set is called the domain of the function and the set is called the codomain of the function. Functions were originally the idealization of how a varying quantity depends on another quantity. For example, the position of a planet is a ''function'' of time. Historically, the concept was elaborated with the infinitesimal calculus at the end of the 17th century, and, until the 19th century, the functions that were considered were differentiable (that is, they had a high degree of regularity). The concept of a function was formalized at the end of the 19th century in terms of set theory, and this greatly increased the possible applications of the concept. A function is often denoted by a letter such as , or . The value of a function at an element of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Polynomial
In mathematics, a polynomial is a mathematical expression consisting of indeterminates (also called variables) and coefficients, that involves only the operations of addition, subtraction, multiplication and exponentiation to nonnegative integer powers, and has a finite number of terms. An example of a polynomial of a single indeterminate is . An example with three indeterminates is . Polynomials appear in many areas of mathematics and science. For example, they are used to form polynomial equations, which encode a wide range of problems, from elementary word problems to complicated scientific problems; they are used to define polynomial functions, which appear in settings ranging from basic chemistry and physics to economics and social science; and they are used in calculus and numerical analysis to approximate other functions. In advanced mathematics, polynomials are used to construct polynomial rings and algebraic varieties, which are central concepts in algebra and algebr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Interpolation
In numerical analysis, multivariate interpolation or multidimensional interpolation is interpolation on ''multivariate functions'', having more than one variable or defined over a multi-dimensional domain. A common special case is bivariate interpolation or two-dimensional interpolation, based on two variables or two dimensions. When the variates are spatial coordinates, it is also known as spatial interpolation. The function to be interpolated is known at given points (x_i, y_i, z_i, \dots) and the interpolation problem consists of yielding values at arbitrary points (x,y,z,\dots). Multivariate interpolation is particularly important in geostatistics, where it is used to create a digital elevation model from a set of points on the Earth's surface (for example, spot heights in a topographic survey or depths in a hydrographic survey). Regular grid For function values known on a regular grid (having predetermined, not necessarily uniform, spacing), the following methods are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Optimization
Multivariate (mathematics), Multivariate is the quality of having multiple variables. It may also refer to: In mathematics * Multivariable calculus * Multivariate function * Multivariate polynomial * Multivariate interpolation * Multivariate optimization In computing * Multivariate cryptography * Multivariate division algorithm * Multivariate optical computing In statistics * Multivariate analysis * Multivariate random variable * Multivariate regression * Multivariate statistics See also * Univariate * Bivariate (other) {{disambiguation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Cryptography
Multivariate cryptography is the generic term for asymmetric cryptographic primitives based on multivariate polynomials over a finite field F. In certain cases, those polynomials could be defined over both a ground and an extension field. If the polynomials have degree two, we talk about multivariate quadratics. Solving systems of multivariate polynomial equations is proven to be NP-complete. That's why those schemes are often considered to be good candidates for post-quantum cryptography. Multivariate cryptography has been very productive in terms of design and cryptanalysis. Overall, the situation is now more stable and the strongest schemes have withstood the test of time. It is commonly admitted that Multivariate cryptography turned out to be more successful as an approach to build signature schemes primarily because multivariate schemes provide the shortest signature among post-quantum algorithms. History presented their so-called C* scheme at the Eurocrypt confe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Division Algorithm
Multivariate is the quality of having multiple variables. It may also refer to: In mathematics * Multivariable calculus * Multivariate function * Multivariate polynomial * Multivariate interpolation * Multivariate optimization In computing * Multivariate cryptography * Multivariate division algorithm * Multivariate optical computing In statistics * Multivariate analysis * Multivariate random variable * Multivariate regression * Multivariate statistics See also * Univariate In mathematics, a univariate object is an expression (mathematics), expression, equation, function (mathematics), function or polynomial involving only one Variable (mathematics), variable. Objects involving more than one variable are ''wikt:multi ... * Bivariate (other) {{disambiguation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Optical Computing
Multivariate optical computing, also known as molecular factor computing, is an approach to the development of compressed sensing spectroscopic instruments, particularly for industrial applications such as process analytical support. "Conventional" spectroscopic methods often employ multivariate and chemometric methods, such as multivariate calibration, pattern recognition, and classification, to extract analytical information (including concentration) from data collected at many different wavelengths. Multivariate optical computing uses an optical computer to analyze the data as it is collected. The goal of this approach is to produce instruments which are simple and rugged, yet retain the benefits of multivariate techniques for the accuracy and precision of the result. An instrument which implements this approach may be described as a multivariate optical computer. Since it describes an approach, rather than any specific wavelength range, multivariate optical computers ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Analysis
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., '' multivariate random variables''. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied. In addition, multivariate statistics is concerned with multivariate probability distributions, in terms of both :*how these can be used to represent the distributions of observed data; :*how they can be used as part of statistical inference, particularly where several different quantities are of interest to the same analysis. Certain types of problems involving multivariate da ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Random Variable
In probability, and statistics, a multivariate random variable or random vector is a list or vector of mathematical variables each of whose value is unknown, either because the value has not yet occurred or because there is imperfect knowledge of its value. The individual variables in a random vector are grouped together because they are all part of a single mathematical system — often they represent different properties of an individual statistical unit. For example, while a given person has a specific age, height and weight, the representation of these features of ''an unspecified person'' from within a group would be a random vector. Normally each element of a random vector is a real number. Random vectors are often used as the underlying implementation of various types of aggregate random variables, e.g. a random matrix, random tree, random sequence, stochastic process, etc. Formally, a multivariate random variable is a column vector \mathbf = (X_1,\dots,X_n)^\mathsf ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Multivariate Regression
The general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In that sense it is not a separate statistical linear model. The various multiple linear regression models may be compactly written as : \mathbf = \mathbf\mathbf + \mathbf, where Y is a matrix with series of multivariate measurements (each column being a set of measurements on one of the dependent variables), X is a matrix of observations on independent variables that might be a design matrix (each column being a set of observations on one of the independent variables), B is a matrix containing parameters that are usually to be estimated and U is a matrix containing errors (noise). The errors are usually assumed to be uncorrelated across measurements, and follow a multivariate normal distribution. If the errors do not follow a multivariate normal distribution, generalized linear models may be used to relax assumptions about Y and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |