pex_acf

<p>Vector of <code>N</code> time points at which the autocorrelation is to be calculated.</p>

tseq

lambda

<p>Power-exponential autocorrelation function.</p>

Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations.  This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300.  Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo.  The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.

Martin Lysy

pex_acf: Power-exponential autocorrelation function.

Description

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Details

Examples