marginal_tau_umv_flat_prior

agabpylib.posteriors.meanvarnormal.marginal_tau_umv_flat_prior(n, V, tau)

Calculate the marginal posterior distribution of tau for the case of unknown mean and unknown variance for flat priors.

Parameters:

• n (int) – The number of data points \(x_i\)

• V (float) – The data variance \(\sum(x_i-\bar{x})^2/n\)

• tau (float array) – 1D-array of \(\tau\) values

Returns:

lnP – The value of ln(posterior) at each grid point.

Return type:

float array