Oliver Linton

TL;DR: A test of the hypothesis of stochastic monotonicity is proposed based on the supremum of a rescaledU-statistic and it is shown that its asymptotic distribution is Gumbel.

TL;DR: In this paper, the authors proposed a nonparametric spectral density estimator for time series models with general autocorrelation, which is a generalization of the well-known prewhitening method of spectral estimation; they argue that this can best be interpreted as multiplicative bias reduction.

TL;DR: In this article, the authors consider nonparametric additive models that have deterministic time trend and both stationary and integrated variables as components, and propose an estimation strategy based on orthogonal series expansion that takes account of the different type of stationarity/nonstationarity possessed by each covariate.

TL;DR: In this article, a survey of the semiparametric and nonparametric methods in univariate and multivariate ARCH/GARCH models is presented, where the authors investigate the estimation techniques applied to: the error density, the functional form of the volatility function, the relationship between mean and variance, long memory processes, locally stationary processes, and continuous time processes.

TL;DR: In this article, the authors investigated the properties of a kernel-type multivariate regression estimator first proposed by Mack and Muller (Sankhya 51:59−72, 1989) in the context of univariate derivative estimation.