Corpus ID: 88516423

A Schur transform for spatial stochastic processes

@article{Mathews2018AST,
  title={A Schur transform for spatial stochastic processes},
  author={J. Mathews},
  journal={arXiv: Statistics Theory},
  year={2018}
}

J. Mathews

Published 2018

Mathematics

arXiv: Statistics Theory

The variance, higher order moments, covariance, and joint moments or cumulants are shown to be special cases of a certain tensor in $V^{\otimes n}$ defined in terms of a collection $X_1,...,X_n$ of $V$-valued random variables, for an appropriate finite-dimensional real vector space $V$. A statistical transform is proposed from such collections--finite spatial stochastic processes--to numerical tuples using the Schur-Weyl decomposition of $V^{\otimes n}$. It is analogous to the Fourier transform… CONTINUE READING

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