منابع مشابه
Directional quantile regression in R
Recently, the eminently popular standard quantile regression has been generalized to the multiple-output regression setup by means of directional regression quantiles in two rather interrelated ways. Unfortunately, they lead to complicated optimization problems involving parametric programming, and this may be the main obstacle standing in the way of their wide dissemination. The presented R pa...
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Although many words have been written about two recent directional (regression) quantile concepts, their applications, and the algorithms for computing associated (regression) quantile regions, their software implementation is still not widely available, which, of course, severely hinders the dissemination of both methods. Wanting to partly fill in the gap here, we provide all the codes needed ...
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This paper sheds some new light on the multivariate (projectional) quantiles recently introduced in Kong and Mizera (2008). Contrary to the sophisticated set analysis used there, we adopt a more parametric approach and study the subgradient conditions associated with these quantiles. In this setup, we introduce Lagrange multipliers which can be interpreted in various interesting ways. We also l...
متن کاملQuantile Regression in R: a Vignette
Quantile regression is an evolving body of statistical methods for estimating and drawing inferences about conditional quantile functions. An implementation of these methods in the R language is available in the package quantreg. This vignette offers a brief tutorial introduction to the package. R and the package quantreg are open-source software projects and can be freely downloaded from CRAN:...
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Belloni, Chernozhukov, and Fernández-Val (2011) developed nonparametric quantile regression methods to estimate and make inference on conditional quantile models. The R package quantreg.nonpar implements these methods for partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonpar...
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ژورنال
عنوان ژورنال: Kybernetika
سال: 2017
ISSN: 0023-5954,1805-949X
DOI: 10.14736/kyb-2017-3-0480