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We introduce an improvement to a periodicity metric we have introduced in a previous paper.We improve on the Hoeffding-test periodicity metric, using the Blum-Kiefer-Rosenblatt (BKR) test. Besides a consistent improvement over the Hoeffding-test approach, the BKR approach turns out to perform superbly when applied to very short time series of sawtoothlike shapes. The expected astronomical implications are much more detections of RR-Lyrae stars and Cepheids in sparse photometric databases, and of eccentric Keplerian radial-velocity (RV) curves, such as those of exoplanets in RV surveys.
I present the Phase Distance Correlation (PDC) periodogram -- a new periodicity metric, based on the Distance Correlation concept of Gabor Szekely. For each trial period PDC calculates the distance correlation between the data samples and their phase
We introduce and test several novel approaches for periodicity detection in unevenly-spaced sparse datasets. Specifically, we examine five different kinds of periodicity metrics, which are based on non-parametric measures of serial dependence of the
We investigate the problem of testing whether $d$ random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two variable Hilbert-Schmidt independence criterion (HSIC) but allows for
We develop multiattribute auctions that accommodate generalized additive independent (GAI) preferences. We propose an iterative auction mechanism that maintains prices on potentially overlapping GAI clusters of attributes, thus decreases elicitation
Dependence measures based on reproducing kernel Hilbert spaces, also known as Hilbert-Schmidt Independence Criterion and denoted HSIC, are widely used to statistically decide whether or not two random vectors are dependent. Recently, non-parametric H