[posterior_mean, posterior_cov] = combine_prior_and_likelihood(prior_mean,prior_cov,data_mean,data_std) combine prior and likelihood information for a vector of variables (on log scale) use formula from convenience kinetics / Bayesian estimation paper Inputs: prior_mean: vector of prior means prior_cov: prior covariance matrix data_mean: data values (one value for each variable) data_std: data standard deviations (one value for each variable) Outputs: posterior_mean: vector of posterior means posterior_cov: posterior covariance matrix