Object Reference : Object View and Procedure Reference : Equation
Display quantile process coefficient estimates (multiple quantile regression estimates).
eq_name.qrprocess(options) [arg] [@coefs coeflist]
where arg is a optional list containing the quantile values (specified using numbers, scalar objects, or vectors) for which you wish to compute estimates, and optionally the @coefs keyword followed by a coeflist of the subset of coefficients to display.
If arg is not specified, EViews will display results for the original equation along with coefficients for equations estimated at a set of equally spaced number of quantiles as specified by the “n=” option. If “n=” is not specified, the default is to display results for the deciles.
If arg is specified, EViews will display results for the original equation along with coefficients for equations estimated at the specified quantiles.
If a coeflist is not provided, results for all coefficients will be displayed. For models that contain an intercept, the coeflist may consist of the @incptonly keyword, indicating that only results for the intercept will be displayed.
You may specify a maximum of 1000 total coefficients (number of display coefficients times the number of quantiles) and a maximum of 500 quantiles.
All estimation will be performed using the settings from the original equation.
n=arg (default=10)
Number of quantiles for process estimates.
Display process estimate results as graph.
size=arg (default=0.95)
Confidence interval size for graph display
Save vector containing test quantile values.
Save matrix containing test coefficient estimates. Each column of the matrix corresponds to a different quantile matching the corresponding quantile in “quantout=”.
To match the covariance matrix given in “covout=” you should take the @vec of the coefficient matrix.
Save symmetric matrix containing covariance matrix for the vector set of coefficient estimates.
Force the dialog to appear from within a program.
Print output.
equation eq1.qreg log(y) c log(x)
estimates a quantile (median) regression of LOG(Y) on a constant and LOG(X), and displays results for all nine quantiles in a table
equation eq1.qreg(quant=.4) log(y) c log(x)
displays the coefficient estimated at the deciles (and at 0.4), and saves the coefficient matrix to COUT.
eq1.qrprocess(coefout=cout, n=4, graph)
eq1.qrprocess(coefout=cout, graph) .25 .5 .75
both estimate coefficients for the three quartiles and display the results in a graph, as does the equivalent:
vector v1(3)
v1.fill .25 .5 .75
eq1.qrprocess(graph) v1
See “Process Coefficients” for a discussion of the quantile process.
See also Equation::qrslope.