Regression

Glad, Ingrid Kristine and Tharmaratnam, Kukatharmini (2015) Regression. In: Encyclopedia of Applied and Computational Mathematics. Springer, Berlin, pp. 1225-1233. ISBN 9783540705284

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Abstract

Regression is a statistical approach for modelling the relationship between a response variable y and one or several explanatory variables x. Various types of regression methods are extensively applied for the analysis of data from literarily all fields of quantitative research. For example, multiple linear regression, logistic regression, and Cox proportional hazards models have been the main basic statistical tools in medical research for decades. In the last 20–30 years, the regression toolbox has been supplied with numerous extensions, like, for example, generalized additive models, regression methods for repeated measurements, and regression methods for high-dimensional data, to mention some.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
78247
Deposited By:
Deposited On:
15 Feb 2016 10:22
Refereed?:
Yes
Published?:
Published
Last Modified:
26 Aug 2020 05:32