The correlation function is a useful signal-analysis tool that engineers often overlook. Its formidable equation, which you have probably not thought about since your undergraduate signals and systems ...

Statistical mechanics provides a fundamental framework for understanding how collective phenomena in many-body systems give rise to macroscopic changes in state, known as phase transitions. Research ...

The autocorrelation, partial and inverse autocorrelation functions described in the preceding sections help when you want to model a series as a function of its past values and past random errors.

This paper considers general linear models for Gaussian geostatistical data with multi-dimensional separable correlation functions involving multiple parameters. We derive various objective priors, ...

In this paper we introduce a simple version of the “local-in-index” correlation model in which the correlation function does not depend on the index but on a synthetic index computed solely from the ...

Almost every day you can find in media commentary that XYZ is causing stocks to fall (or rise). Such definitive statements are common—but what’s almost always missing is statistical proof. And if you ...

This paper introduces long-range dependence for a stationary random field on a plane lattice, derives an exact power-law correlation model and other models with long-range dependence on the lattice, ...

Two-time correlation functions of the ce-based MG measured by HP-XPCS at different pressures during compression. At each pressure, the width of the reddish diagonal contour is proportional to the ...