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Regression and Correlation Analysis
1987Correlation is a tool for understanding the relationship between two quantities. Regression considers how one quantity is influenced by another. In correlation analysis the two quantities are considered symmetrically: in regression analysis one is supposed dependent on the other, in an unsymmetric way. Extensions to sets of quantities are important.
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2008
Abstract : In regression analysis, the goal is to determine the values of parameters for a function to best fit a set of data observations. Put another way, regression attempts to best describe what inputs result in a given output. Though there are many complex forms of regression models, the simplest is a linear regression model.
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Abstract : In regression analysis, the goal is to determine the values of parameters for a function to best fit a set of data observations. Put another way, regression attempts to best describe what inputs result in a given output. Though there are many complex forms of regression models, the simplest is a linear regression model.
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Regression Analysis by Example.
Journal of the American Statistical Association, 1979B. Price +2 more
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The Analysis of Disturbances in Regression Analysis
Journal of the American Statistical Association, 1965Classical regression analysis is concerned with the estimation of the parameter vector\(beta \)of the equation\(y = X\beta + u\)(1.1)where y is the T-element column vector of values taken by the dependent variable, X the \(TxA\) matrix of values taken by the A independent variables, \(beta \) a column of A parameters, and u a column of T disturbance.
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2019
Principal Component Analysis (PCA) is a widely used dimensional reduction method that aims to find a low dimension sub space of highly correlated data for its major information to be used in further analysis. Machine learning methods based on PCA are popular in high dimensional data analysis, such as video and image processing. In video processing, the
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Principal Component Analysis (PCA) is a widely used dimensional reduction method that aims to find a low dimension sub space of highly correlated data for its major information to be used in further analysis. Machine learning methods based on PCA are popular in high dimensional data analysis, such as video and image processing. In video processing, the
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Metabolomics in cancer research and emerging applications in clinical oncology
Ca-A Cancer Journal for Clinicians, 2021Daniel R Schmidt +2 more
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