Spatial analysis | Covariance and correlation

Rational quadratic covariance function

In statistics, the rational quadratic covariance function is used in spatial statistics, geostatistics, machine learning, image analysis, and other fields where multivariate statistical analysis is conducted on metric spaces. It is commonly used to define the statistical covariance between measurements made at two points that are d units distant from each other. Since the covariance only depends on distances between points, it is stationary. If the distance is Euclidean distance, the rational quadratic covariance function is also isotropic. The rational quadratic covariance between two points separated by d distance units is given by where α and k are non-negative parameters of the covariance. * v * t * e (Wikipedia).

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From playlist Quadratic Functions and Equations

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From playlist Machine Learning

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From playlist Graphing Quadratic Functions

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From playlist Seminar on Applied Geometry and Algebra (SIAM SAGA)

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http://mathispower4u.wordpress.com/

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From playlist Machine Learning Tutorials

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From playlist Machine Learning Tutorials

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Related pages

Covariance function | Parameter | Metric space | Stationary process | Euclidean distance | Statistics | Covariance