statistical regression

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  • noun

Synonyms for statistical regression

the relation between selected values of x and observed values of y (from which the most probable value of y can be predicted for any value of x)

References in periodicals archive ?
The second release will use statistical regression formulas, similar to those currently used by the Federal Reserve Bank, to allow lenders to performing in-depth self-testing analysis.
There are successful implementations built on methods ranging from traditional statistical regression to machine learning and data mining techniques.
To this end, we seek to revolutionize scientific and practical modi operandi of data acquisition and learning by developing a new optimization and analysis framework based on the nascent low-dimensional models with broad applications from inverse problems to analog-to-information conversion, and from automated representation learning to statistical regression.
However, all advanced computer-driven methods and statistical regression are firmly within the inferential branch of statistics.
Among his topics are two basic data mining methods for variable assessment, the importance of the regressional coefficient, market segmentation classification modeling with logistic regression, a comparison of genetic and statistical regression models, and interpreting coefficient-free models.
In order to investigate the relationship between tree cover variables in forest ecology studies, statistical regression method are used.
After an eight-month development process, the result has been the creation of a product that uses actuarial and statistical regression techniques to provide clients and prospects with a full distribution of securities class-action settlement amounts--including average, median and worst-ease values--using client-specific independent variables such as market capitalization, industry sector, price/earnings ratio and total assets.
The spectra of the samples were matched with the composition and quality data to develop multivariate statistical regression and classification models.
Chapters cover differentiation, integration, series and limits, functions defined by integrals, complex numbers, ordinary differential equations, power series solutions of differential equations, orthogonal polynomials, Fourier series, Fourier transforms, operators, functions of several variables, vectors, plane polar coordinates and spherical coordinates, the classical wave equation, the Schrodinger equation, determinants, matrices, matrix eigenvalue problems, vector spaces, probability, statistical regression and correlation, and numerical methods.
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