Covariance estimation for stochastic processes

Estimating the thing that is given to you by oracles in statistics homework assignments: the covariance, precision matrices of things, or, if you data is indexed in some fashion, the covariance kernel. A complement to Gaussian process simulation.

I am not doing a complete theory of covariance estimation here, just mentioning a couple of tidbits for future reference.


Wishart priors. 🏗

Sandwich estimators

For robust covariances of vector data. AKA Heteroskedasticity-consistent covariance estimators. Incorporating Eicker-Huber-White sandwich estimator, Andrews kernel HAC estimator, Newey-West and others. For an intro see Achim Zeileis, Open-Source Econometric Computing in R.

Parametric covariance functions

Fun covariance models.

To read


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