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quantreg (version 4.77)

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

Value

  • tausThe points of evaluation of the process
  • qtausValues of xbar'betahat(taus)
  • VhatJoint parametric QR process
  • vhatMarginal parametric QR processes

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.

See Also

KhmaladzeTest