Parameters for image inv_model.gaussian_prior_likelihood.img_mean -> image mean inv_model.gaussian_prior_likelihood.R_prior -> L*L' = inv(image covariance) inv_model.gaussian_prior_likelihood.img_exp -> ( default = 2) Parameters for data inv_model.gaussian_prior_likelihood.Noise -> L*L' = inv(Noise covariance) inv_model.gaussian_prior_likelihood.data_exp -> ( default = 2) Function to be used with mcmc_solve
0001 function likelihood= gaussian_prior_likelyhood( varargin ) 0002 % Parameters for image 0003 % inv_model.gaussian_prior_likelihood.img_mean -> image mean 0004 % inv_model.gaussian_prior_likelihood.R_prior -> L*L' = inv(image covariance) 0005 % inv_model.gaussian_prior_likelihood.img_exp -> ( default = 2) 0006 % Parameters for data 0007 % inv_model.gaussian_prior_likelihood.Noise -> L*L' = inv(Noise covariance) 0008 % inv_model.gaussian_prior_likelihood.data_exp -> ( default = 2) 0009 % 0010 % Function to be used with mcmc_solve 0011 0012 % (C) 2007 Nick Polydorides. License: GPL version 2 or version 3 0013 % $Id: gaussian_prior_likelyhood.m 3289 2012-07-01 10:40:31Z aadler $ 0014 0015 warning('EIDORS:deprecated','GAUSSIAN_PRIOR_LIKELYHOOD is deprecated as of 08-Jun-2012. Use PRIOR_GAUSSIAN_LIKELIHOOD instead.'); 0016 0017 if isfield(inv_model,'gaussian_prior_likelyhood'); 0018 inv_model.prior_gaussian_likelihood = inv_model.gaussian_prior_likelyhood; 0019 end 0020 0021 likelihood = prior_gaussian_likelihood(varargin{:});