qrprocess |

Display quantile process coefficient estimates (multiple quantile regression estimates).

Syntax

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.

Options

n=arg (default=10) | Number of quantiles for process estimates. |

graph | Display process estimate results as graph. |

size=arg (default=0.95) | Confidence interval size for graph display |

quantout=name | Save vector containing test quantile values. |

coefout=name | 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. |

covout=name | Save symmetric matrix containing covariance matrix for the vector set of coefficient estimates. |

prompt | Force the dialog to appear from within a program. |

p | Print output. |

Examples

equation eq1.qreg log(y) c log(x)

eq1.qrprocess

estimates a quantile (median) regression of LOG(Y) on a constant and LOG(X), and displays results for all nine quantiles in a table

Similarly,

equation eq1.qreg(quant=.4) log(y) c log(x)

eq1.qrprocess(coefcout=cout)

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

Cross-references

See
“Process Coefficients” for a discussion of the quantile process.

See also
Equation::qrcrprocess and
Equation::qrecprocess.