Predicting high sensitivity C-reactive protein levels and their associations in a large population using decision tree and linear regression. [PDF]
Sci RepGhiasi Hafezi S +9 more
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Investigations via Kinetics and Multivariate Linear Regression Models of the Mechanism and Origins of Regioselectivity in a Palladium-Catalyzed Aryne Annulation. [PDF]
ACS CatalPlasek EE, Denman BN, Roberts CC.
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Inequalities in accelerated cognitive decline: Resolving observational window bias using nested non-linear regression. [PDF]
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A Linear Regression Approach for Best Scanline Determination in the Object to Image Space Transformation Using Pushbroom Images. [PDF]
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Inference and diagnostics for censored linear regression model with skewed generalized <i>t</i> distribution. [PDF]
J Appl StatLian C +4 more
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The baboon as a statistician: Can non-human primates perform linear regression on a graph?
Ciccione L +4 more
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AbstractLinear regression plays a fundamental role in statistical modeling. This article provides a step‐by‐step coverage of linear models in the order of model specification, model estimation, statistical inference, variable selection, model diagnosis, and prediction. Computation issues in linear regression and intimately relevant extensions of linear
Su, Xiaogang, Yan, Xin, Tsai, Chih Ling
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On the linearity of regression
Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1982A stochastic process X={X t :t∈T| is called spherically generated if for each random vector $$X = (X_{t_1 } , \ldots ,X_{t_n } )$$ , there exist a random vector Y=(Y1,..., Y m) with a spherical (radially symmetric) distribution
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