Zobrazeno 1 - 10
of 216
pro vyhledávání: '"Werker, Bas"'
We study the effectiveness of subagging, or subsample aggregating, on regression trees, a popular non-parametric method in machine learning. First, we give sufficient conditions for pointwise consistency of trees. We formalize that (i) the bias depen
Externí odkaz:
http://arxiv.org/abs/2404.01832
The classical concept of bounded completeness and its relation to sufficiency and ancillarity play a fundamental role in unbiased estimation, unbiased testing, and the validity of inference in the presence of nuisance parameters. In this short note,
Externí odkaz:
http://arxiv.org/abs/2308.00895
Autor:
Werker, Bas, Zhou, Bo
We address the issue of semiparametric efficiency in the bivariate regression problem with a highly persistent predictor, where the joint distribution of the innovations is regarded an infinite-dimensional nuisance parameter. Using a structural repre
Externí odkaz:
http://arxiv.org/abs/2009.08291
Autor:
Jansen, Kristy A. E.1 (AUTHOR) kjansen@marshall.usc.edu, Werker, Bas J. M.2 (AUTHOR) b.j.m.werker@tilburguniversity.edu
Publikováno v:
Journal of Financial & Quantitative Analysis. Nov2022, Vol. 57 Issue 7, p2693-2723. 31p.
We propose a new class of unit root tests that exploits invariance properties in the Locally Asymptotically Brownian Functional limit experiment associated to the unit root model. The invariance structures naturally suggest tests that are based on th
Externí odkaz:
http://arxiv.org/abs/1806.09304
Autor:
Werker, Bas J.M., Zhou, Bo
Publikováno v:
In Journal of Econometrics April 2022 227(2):347-370
Publikováno v:
Working Papers: U.S. Federal Reserve Board's Finance & Economic Discussion Series; Mar2024, p1-53, 53p
Publikováno v:
The Annals of Statistics, 2019 Oct 01. 47(5), 2601-2638.
Externí odkaz:
https://www.jstor.org/stable/26784040
Publikováno v:
Annals of Statistics 2014, Vol. 42, No. 5, 1911-1940
We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step update of a
Externí odkaz:
http://arxiv.org/abs/1306.6658
Publikováno v:
Bernoulli 2009, Vol. 15, No. 2, 297-324
This paper considers non-negative integer-valued autoregressive processes where the autoregression parameter is close to unity. We consider the asymptotics of this `near unit root' situation. The local asymptotic structure of the likelihood ratios of
Externí odkaz:
http://arxiv.org/abs/0906.2080