Abstract The portmanteau test provides the vanilla method for detecting serial correlations in classical univariate time series analysis. is extended to case of observations from a locally stationary functional series. Asymptotic critical values are obtained by suitable block multiplier bootstrap procedure. shown asymptotically hold its level and be consistent against general alternatives.

We consider a zero mean discrete time series, and define its discrete Fourier transform at the canonical frequencies. It is well known that the discrete Fourier transform is asymptotically uncorrelated at the canonical frequencies if and if only the time series is second order stationary. Exploiting this important property, we construct a Portmanteau type test statistic for testing stationarity...

Across five experiments this study investigated the disparity tuning of the stereoscopic motion aftereffect (adaptation from moving retinal disparity). Adapting and test stimuli were moving and stationary stereoscopic grating patterns, respectively, created from dynamic random-dot stereograms. Observers adapted to moving stereoscopic grating patterns presented with a given disparity and viewed ...

We suggest a rescaled variance type test for stationarity (null hypothesis) against deterministic trends and unit roots. The asymptotic (parameter free) distribution of the test is derived and critical values tabulated by simulations for a wide class of stationary errors with short, long or negative dependence structure. The proposed test detects a deterministic trend that can be presented as a...

We propose a test for testing the equality of several high-dimensional covariance matrices stationary processes with general distribution. The asymptotic distribution proposed is proved to be χ2 Both numerical simulation and empirical study illustrate that has perfect performance, in particular, its power can approach 1 on set three known distributions.