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Handbook of Quantile Regression by Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng is a nonfiction available to read on EtoBox.

What is Handbook of Quantile Regression about?

Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volum

Who reads Handbook of Quantile Regression?

Author

Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng

Publisher

Chapman and Hall/CRC;CRC Press

Published

2018

Language

EN

ISBN

9781351637039

Category

nonfiction

Subjects

Mathematics, Stem