Work

R-estimation in a Linear Model with Autoregressive Errors

Year: 2026

Type: preprint

Abstract: In the linear regression model, we construct a nonparametric estimate of the regression parameter vector $\boldgreekβ$ that is insensitive to a possible nuisance autoregression in the model errors. The main tool for estimating $\boldgreekβ$ is based on the autoregression rank scores of the model. The resulting estimator is invariant to the autoregression parameters and thus remains insensitive to potential hidden linear trends or other structured disturbances, which frequently occur in economic, hydrological, and related applications.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2608.13150

Authors: Jurečková, Jana, Koul, Hira, Picek, Jan

Institutions: Czech Academy of Sciences, Czech Academy of Sciences, Institute of Information Theory and Automation, Michigan State University, Technical University of Liberec

Topic: Advanced Statistical Methods and Models

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funder: Grantová Agentura České Republiky

Award: Aggregation of Methodologies Based on Economic Data

OpenAlex ID: W7203464313

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