em_gauss

Purpose

Recomputes the (Gaussian) noise variance.

Synopsis

[newLikPar] = em_gauss(oldLikPar,y,cavM,cavV,postM,postV);

Description

[newLikPar] = em_gauss(oldLikPar,y,cavM,cavV,postM,postV) - implements the M-step in the GP inference assuming Gaussian additive noise. The data is assumed to be factorising, thus we have a direct result as

newLikPar  = sum(postV + (y-postM).^2) / N

where N is the number of training samples.

Parameters:

oldLikPar

- preceeding value of the likelihood parameter.

y

- training output.

cavM,cavV

- (cavity) mean and variance of the GP.

postM,postV

- mean and variance of the posterior process.

newLikPar

- the new noise variance.

See Also

ogptrain, demogp_reg, c_reg_gauss, g_l_gauss

Copyright (c) Lehel Csató (2001-2004)