General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaced by DP 2007-65)

Research output: Working paperDiscussion paperOther research output

Abstract

High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which uni¯es and extends many existing robust procedures. We derive here the consistency and asymptotic distri- bution of the proposed general trimmed estimator under mild ¯-mixing conditions and demonstrate its applicability in nonlinear regression, time series, and limited dependent variable models.
Original languageEnglish
Place of PublicationTilburg
PublisherEconometrics
Number of pages44
Volume2007-1
Publication statusPublished - 2007

Publication series

NameCentER Discussion Paper
Volume2007-1

Fingerprint

Robust Estimation
Estimator
Dependent
Least Trimmed Squares
Breakdown Point
Mixing Conditions
Nonlinear Regression
Regression Estimator
Asymptotic distribution
Likelihood
Time series
Model
Demonstrate

Keywords

  • asymptotic normality
  • regression
  • robust estimation
  • trimming

Cite this

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title = "General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaced by DP 2007-65)",
abstract = "High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which uni¯es and extends many existing robust procedures. We derive here the consistency and asymptotic distri- bution of the proposed general trimmed estimator under mild ¯-mixing conditions and demonstrate its applicability in nonlinear regression, time series, and limited dependent variable models.",
keywords = "asymptotic normality, regression, robust estimation, trimming",
author = "P. Cizek",
note = "Pagination: 44",
year = "2007",
language = "English",
volume = "2007-1",
series = "CentER Discussion Paper",
publisher = "Econometrics",
type = "WorkingPaper",
institution = "Econometrics",

}

General Trimmed Estimation : Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaced by DP 2007-65). / Cizek, P.

Tilburg : Econometrics, 2007. (CentER Discussion Paper; Vol. 2007-1).

Research output: Working paperDiscussion paperOther research output

TY - UNPB

T1 - General Trimmed Estimation

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AU - Cizek, P.

N1 - Pagination: 44

PY - 2007

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N2 - High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which uni¯es and extends many existing robust procedures. We derive here the consistency and asymptotic distri- bution of the proposed general trimmed estimator under mild ¯-mixing conditions and demonstrate its applicability in nonlinear regression, time series, and limited dependent variable models.

AB - High breakdown-point regression estimators protect against large errors and data con- tamination. Motivated by some { the least trimmed squares and maximum trimmed like- lihood estimators { we propose a general trimmed estimator, which uni¯es and extends many existing robust procedures. We derive here the consistency and asymptotic distri- bution of the proposed general trimmed estimator under mild ¯-mixing conditions and demonstrate its applicability in nonlinear regression, time series, and limited dependent variable models.

KW - asymptotic normality

KW - regression

KW - robust estimation

KW - trimming

M3 - Discussion paper

VL - 2007-1

T3 - CentER Discussion Paper

BT - General Trimmed Estimation

PB - Econometrics

CY - Tilburg

ER -