We consider goodness‐of‐fit tests for the multivariate Student's t‐distribution with iid data
and for the innovation distribution in a generalized autoregressive conditional …

Change point detection in high dimensional data has found considerable interest in recent
years. Most of the literature either designs methodology for a retrospective analysis, where …

While averaging unrestricted with restricted estimators is known to reduce estimation risk, it
is an open question whether this reduction in turn can improve inference. To analyze this …

On Sobolev tests of uniformity on the circle with an extension to the sphere Page 1 Bernoulli 26(3),
2020, 2226–2252 https://doi.org/10.3150/19-BEJ1191 On Sobolev tests of uniformity on the circle …

In this paper, we develop statistical inference tools for high-dimensional functional time
series. We introduce a new concept of physical dependent processes in the space of square …

In this article, we propose a new projection test for linear hypotheses on regression
coefficient matrices in linear models with high-dimensional responses. We systematically …

We propose an asset pricing factor model constructed with semiparametric characteristics-
based mispricing and factor loading functions. We approximate the unknown functions by B …

We develop a powerful quadratic test for the overall significance of many covariates in a
dense regression model in the presence of nuisance parameters. By equally weighting the …

This article proposes an overidentifying restriction test for high-dimensional linear
instrumental variable models. The novelty of the proposed test is that it allows the number of …

Tests based on the $2 $-and $\infty $-norm have received considerable attention in high-
dimensional testing problems, as they are powerful against dense and sparse alternatives …