Arbeitspapier

Quantile regression estimates for a class of linear and partially linear errors-in-variables models

We consider the problem of estimating quantile regression coefficients in errors-in-variables models. When the error variables for both the response and the manifest variables have a joint distribution that is spherically symmetric but otherwise unknown, the regression quantile estimates based on orthogonal residuals are shown to be consistent and asymptotically normal. We also extend the work to partially linear models when the response is related to some additional covariate.

Language: Englisch

Bibliographic citation: Series: SFB 373 Discussion Paper ; No. 1997,103

Classification: Wirtschaft

Subject: semiparametric model
Kernel
linear regression
errors-in-variables
regression quantile

Event: Geistige Schöpfung

(who): He, Xuming
Liang, Hua

Event: Veröffentlichung

(who): Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

(where): Berlin

(when): 1997

Handle: http://hdl.handle.net/10419/66276

URN: urn:nbn:de:kobv:11-10064800

Last update: 10.03.2025, 11:44 AM CET

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Object type

Arbeitspapier

Associated

He, Xuming
Liang, Hua
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Time of origin

1997

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Quantile regression estimates for a class of linear and partially linear errors-in-variables models

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Other Objects (12)

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