quantreg: rqProcess – R documentation

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rqProcess

Compute Standardized Quantile Regression Process

Description

Computes a standardize quantile regression process for the model specified by the formula, on the partition of [0,1] specified by the taus argument, and standardized according to the argument nullH. Intended for use in KhmaladzeTest.

Usage

rqProcess(formula, data, taus, nullH = "location", ...)

Arguments

`formula`	model formula
`data`	data frame to be used to interpret formula
`taus`	quantiles at which the process is to be evaluated, if any of the taus lie outside (0,1) then the full process is computed for all distinct solutions.
`nullH`	Null hypothesis to be used for standardization
`...`	optional arguments passed to `summary.rq`

Details

The process computes standardized estimates based on the hypothesis specified in the nullH argument. The Vhat component is rescaled by the Cholesky decomposition of the tau specific covariance matrix, the vhat component is rescaled by the marginal standard errors. The nature of the covariance matrix used for the standardization is controlled arguments passed via the ... argument to summary.rq. If the full process is estimated then these covariance options aren't available and only a simple iid-error form of the covariance matrix is used.

Value

`taus`	The points of evaluation of the process
`qtaus`	Values of xbar'betahat(taus)
`Vhat`	Joint parametric QR process
`vhat`	Marginal parametric QR processes

Author(s)

R. Koenker

Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Blaise Melly [ctb] (Contributions to preprocessing code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Cleve Moler [ctb] (author of several linpack routines), Yousef Saad [ctb] (author of sparskit2), Victor Chernozhukov [ctb] (contributions to extreme value inference code), Ivan Fernandez-Val [ctb] (contributions to extreme value inference code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)

Initial release