*! version 1.0.0 14jul2018

Title

cdfquantreg_p -- Postestimation tools for cdfquantreg

Description

The following postestimation commands are available after cdfquantreg:

Command Description

margins margins commands for cdfquantreg

predict predictions, residuals

Syntax for predict

predict newvar [if] [in] [, [stdp|qtile|pctle(real #)]]

statistic

Main
xb linear prediction of the location parameter; the default

xd linear prediction of the dispersion parameter; the default

seb standard error of the location linear prediction

sed standard error of the dispersion linear prediction

qtile either the empirical or requested quantile rank

fitted fitted observations corresponding to qtile

residuals differences between fitted and y

Options for predict

Main

stdp calculates the standard errors of the linear predictions for
both the location and dispersion submodels.

qtile calculates fitted values for the dependent variable, either
corresponding to the quantile rank of each observation or (in combination with
pctle(#)) corresponding to a specified quantile rank.

pctle(#) is allowed only in combination with qtile, and specifies
the quantile that predict is to estimate. It expects a number in the
(0,1) interval. To estimate the median, for instance, # would be set to 0.5.

Examples for predict

/* This example uses testmat1.dta */

. cdfquantreg y i.d1##i.d2, cdf(t2) quantile(t2) zvarlist(d1 d2)

. predict newvar, qtile

. drop newvar xd fitted residuals

. predict newvar, qtile pctle(0.5)

Margins

The margins command requires specifying which equation is to be estimated.
Thus, equation(1) refers to the location submodel and equation(2)
refers to the dispersion submodel. Examples of appropriate syntax are:

margins varname , predict(equation(eqno))
margins dydx(varname) , predict(equation(eqno))

Examples for margins

/* This example uses testmat1.dta */

. cdfquantreg y i.d1##i.d2, cdf(t2) quantile(t2) zvarlist(d1 d2)

. margins d2, predict(equation(#1))

. margins, dydx(1.d2) predict(equation(#1))

. margins d2, expression(exp(predict(equation(#2))))

Author

Michael Smithson, Research School of Psychology, The Australian National University,
Canberra, A.C.T. Australia
Michael.Smithson@anu.edu.au

References

Smithson, M. & Shou, Y. (2017). CDF-quantile distributions for modeling random
variables on the unit interval. British Journal of Mathematical and Statistical Psychology, 70(3), 412-438.

Shou, Y. & Smithson, M. (2019). cdfquantreg: An R package for
CDF-Quantile Regression. Journal of Statistical Software, 88, 1-30.