We review some statistical aspects of distance covariance/correlation function and we demonstrate its applicability to time series analysis. We will see that the auto-distance covariance/correlation function is able to identify nonlinear relationships and can be employed for testing the i.i.d.\\ ...
Euclidean distance or Dynamic Time Warping distance [1, 2]• Matching features of the series e.g. autocorrelation coef f i cients [3], Pearson correlation coef f i cients [4], peri-odograms [5], extreme value behavior [6]• Number of matching subsequences in the series [7]• ...
vector time serieswind forecastingzonal polynomialSz\\'{e}kely, Rizzo and Bakirov (Ann. Statist. 35 (2007) 2769-2794) andSz\\'{e}kely and Rizzo (Ann. Appl. Statist. 3 (2009) 1236-1265), in two seminalpapers, introduced the powerful concept of distance correlation as a measure of...
Applications of distance correlation to time series The use of empirical characteristic functions for inference problems, including estimation in some special parametric settings and testing for goodness of ... R Davis,M Matsui,TV Mikosch,... - Bernoulli Society for Mathematical Statistics and Probabili...
[1] Chang D J , Desoky A H , Ming O , et al. Compute Pairwise Manhattan Distance and Pearson Correlation Coefficient of Data Points with GPU[C]// 10th ACIS International Conference on Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, SNPD 2009, in ...
The distance is corrected for correlation. Consider Fig. 30.4a; the distance between the centre C of the cluster and the objects A and B is the same in Euclidean distances but, since B is part of the group of objects outlined by the ellipse, while A is not, one would like a distance...
correlation distance [‚kär·ə′lā·shən ‚dis·təns] (communications) In tropospheric scatter propagation, the minimum spatial separation between antennas which will give rise to independent fading of the received signals. McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Co...
Identifying financial time series with similar dynamic conditional correlation The approach is based on a clustering algorithm, which uses the idea of distance between dynamic conditional correlations, and the classical Wald test, to... E Otranto - 《Computational Statistics & Data Analysis》 被引量...
Alternatively, correlation tracking analysis of mesogranular scales of motion applied to the same time series is used to deduce the near-surface flow field. These two approaches provide the means to assess the patterns and evolution of horizontal flows on supergranular scales even near disk center,...
A fast general purpose algorithm for the computation of auto- and cross-correlation integrals from single channel data We developed an optimized algorithm that allows computation of auto- and cross-correlation integrals from single channel time series without restricting th... G Widman,K Lehnertz,P...