Poissonian correlation of higher order differences

Higher Order Correlation coefficients

Higher-Order Risk Attitudes toward Correlation

Higher-order risk attitudes other than risk aversion (e.g., prudence and temperance) play vital roles both in theoretical and empirical work. While the literature has mainly focused on how they entail a preference for combining “good” outcomes with “bad” outcomes, We consider here an alternative approach which relates higher-order risk attitudes to the sign of correlation. The theoretical resul...

Higher-Order Correlation Clustering for Image Segmentation

For many of the state-of-the-art computer vision algorithms, image segmentation is an important preprocessing step. As such, several image segmentation algorithms have been proposed, however, with certain reservation due to high computational load and many hand-tuning parameters. Correlation clustering, a graphpartitioning algorithm often used in natural language processing and document cluster...

Reconstructing attractors with higher order correlation

| We propose a novel criterion of deciding time delays for reconstructing attractors from a single variable time series. Our criterion considers higher order correlation functions, and nds the convergence values of the extrema. In order to see how our method works well, we analyze two numerical examples by observing the shapes of reconstructed attractors and calculating phase space continuities...

Modeling and analyzing higher-order correlations in non-Poissonian spike trains.

Measuring pairwise and higher-order spike correlations is crucial for studying their potential impact on neuronal information processing. In order to avoid misinterpretation of results, the tools used for data analysis need to be carefully calibrated with respect to their sensitivity and robustness. This, in turn, requires surrogate data with statistical properties common to experimental spike ...