marginal_mean_umv_uninf_prior#
- agabpylib.posteriors.meanvarnormal.marginal_mean_umv_uninf_prior(n, xbar, V, mu)#
Calculate the marginal posterior distribution of :math`mu` for the case of unknown mean and unknown variance and with an uninformative prior on \(\tau\).
- Parameters:
n (int) – The number of data points \(x_i\)
xbar (float) – The mean of the data points \(x_i\)
V (float) – The data variance \(\sum(x_i-\bar{x})^2/n\)
mu (float array) – 1D-array of \(\mu\) values
- Returns:
lnP – The value of ln(posterior) at each grid point.
- Return type:
float array