deriv_wn: Analytic D matrix white noise process
In gmwm: Generalized Method of Wavelet Moments

Analytic D matrix white noise process

1	deriv_wn(tau)

tau

A vec that contains the scales to be processed (e.g. 2^(1:J))

The haar wavelet variance is given as nu^2(tau) = sigma_0^2 / tau. Taking the derivative with respect to sigma_0^2 yields: 1/tau

A matrix with the first column containing the partial derivative with respect to sigma[0]^2.

JJB

1	deriv_wn(2^(1:5))

gmwm documentation built on April 14, 2017, 4:38 p.m.

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