Prior for the coefficients of a linear regression model

I have a linear regression model \bf Y=\bf{X}\bf{\beta}+\epsilon. I want to assign a prior on \bf\beta in order to derive the posterior predictive model p(y_{predictive}|\bf{y},\bf{X},\beta). How do I decide which prior I assign to the regression coefficient \bf{\beta} ? Is there a literature that discusses this?


A nice document with general advice on choosing priors (with links to papers with more detail) is here:

Source : Link , Question Author : Spandyie , Answer Author : Greg Snow

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