A2 Vertaisarvioitu katsausartikkeli tieteellisessä lehdessä
Robust Nonparametric Inference
Tekijät: Nordhausen K, Oja H
Kustantaja: ANNUAL REVIEWS
Julkaisuvuosi: 2018
Journal: Annual Review of Statistics and Its Application
Tietokannassa oleva lehden nimi: ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 5
Lehden akronyymi: ANNU REV STAT APPL
Vuosikerta: 5
Aloitussivu: 473
Lopetussivu: 500
Sivujen määrä: 28
ISSN: 2326-8298
eISSN: 2326-831X
DOI: https://doi.org/10.1146/annurev-statistics-031017-100247
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/31111091
In this article, we provide a personal review of the literature on nonparametric and robust tools in the standard univariate and multivariate location and scatter, as well as linear regression problems, with a special focus on sign and rank methods, their equivariance and invariance properties, and their robustness and efficiency. Beyond parametric models, the population quantities of interest are often formulated as location, scatter, skewness, kurtosis and other functionals. Some old and recent tools for model checking, dimension reduction, and subspace estimation in wide semiparametric models are discussed. We also discuss recent extensions of procedures in certain nonstandard semiparametric cases including clustered and matrix-valued data. Our personal list of important unsolved and future issues is provided.
Ladattava julkaisu This is an electronic reprint of the original article. |