rqProcess

0th

Percentile

Compute Standardized Quantile Regression Process

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.

Keywords
regression
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

See Also

KhmaladzeTest

Aliases
  • rqProcess
Documentation reproduced from package quantreg, version 5.54, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.