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- W4256294872 abstract "This chapter introduces the notion of linear regressions and implements it within q. The linear regression model should be a starting point for nearly any problem where people want to establish a relationship between factors on one side and a dependent variable on the other side. The linear regression is in nature close to understanding the correlation between variables. The chapter provides the theory underlying the linear regression models and discusses its limitations. Following the underlying implementation, the chapter discusses several advanced topics related to linear regression. It aims to unite the code elements into an estimation suite which presents an alternative to linear regression toolboxes in other programming languages. The chapter also defines several additional features, which complement the statistical information about the estimates and the estimated model. It explains how to calculate the ordinary least squares estimates of the parameters of a linear model." @default.
- W4256294872 created "2022-05-12" @default.
- W4256294872 date "2019-11-04" @default.
- W4256294872 modified "2023-10-18" @default.
- W4256294872 title "Linear Regression" @default.
- W4256294872 doi "https://doi.org/10.1002/9781119404729.ch13" @default.
- W4256294872 hasPublicationYear "2019" @default.
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