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Regression

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Regression. / Glad, Ingrid Kristine; Tharmaratnam, Kukatharmini.
Encyclopedia of Applied and Computational Mathematics. ed. / Björn Engquist. Berlin: Springer, 2015. p. 1225-1233.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter (peer-reviewed) › peer-review

Harvard

Glad, IK & Tharmaratnam, K 2015, Regression. in B Engquist (ed.), Encyclopedia of Applied and Computational Mathematics. Springer, Berlin, pp. 1225-1233. https://doi.org/10.1007/978-3-540-70529-1_420

APA

Glad, I. K., & Tharmaratnam, K. (2015). Regression. In B. Engquist (Ed.), Encyclopedia of Applied and Computational Mathematics (pp. 1225-1233). Springer. https://doi.org/10.1007/978-3-540-70529-1_420

Vancouver

Glad IK, Tharmaratnam K. Regression. In Engquist B, editor, Encyclopedia of Applied and Computational Mathematics. Berlin: Springer. 2015. p. 1225-1233 doi: 10.1007/978-3-540-70529-1_420

Author

Glad, Ingrid Kristine ; Tharmaratnam, Kukatharmini. / Regression. Encyclopedia of Applied and Computational Mathematics. editor / Björn Engquist. Berlin : Springer, 2015. pp. 1225-1233

Bibtex

@inbook{3cd8928c90a947e38a91f653b5ca54ad,
title = "Regression",
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.",
author = "Glad, {Ingrid Kristine} and Kukatharmini Tharmaratnam",
year = "2015",
month = nov,
day = "21",
doi = "10.1007/978-3-540-70529-1_420",
language = "English",
isbn = "9783540705284",
pages = "1225--1233",
editor = "Engquist, {Bj{\"o}rn }",
booktitle = "Encyclopedia of Applied and Computational Mathematics",
publisher = "Springer",

}

RIS

TY - CHAP

T1 - Regression

AU - Glad, Ingrid Kristine

AU - Tharmaratnam, Kukatharmini

PY - 2015/11/21

Y1 - 2015/11/21

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-540-70529-1_420

DO - 10.1007/978-3-540-70529-1_420

M3 - Chapter (peer-reviewed)

SN - 9783540705284

SP - 1225

EP - 1233

BT - Encyclopedia of Applied and Computational Mathematics

A2 - Engquist, Björn

PB - Springer

CY - Berlin

ER -