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Handbook of Quantile Regression (Paperback)
Loot Price: R1,568
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Handbook of Quantile Regression (Paperback)
Series: Chapman & Hall/CRC Handbooks of Modern Statistical Methods
Expected to ship within 12 - 17 working days
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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 volume is to provide
a comprehensive review of recent developments of quantile
regression methodology illustrating its applicability in a wide
range of scientific settings. The intended audience of the volume
is researchers and graduate students across a diverse set of
disciplines.
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