can mr use nonzero coefficient why is the prior scale used why is the prior scale multiplied by nonzero observations is it common to overfit a predictor why do predictors take on zeros what does it mean to multiply the prior scale by the fraction of nonzero observations? when multiplying the prior scale by fraction of nonzero observations, the underlying model is _______. why is this necessary for a multivariate regression model why are gaussian priors important why is it called the common sense to multiply prior scale by fraction of non zero observations? what does it mean when a prior is nonzero why does the prior scale change for a predictor why does it not seem to be standard to multiply prior scale by fraction of nonzero observations? why is it implausible to use a prior for a predictor why would you not multiply prior scale by fraction of nonzero predictors? why do you have to use a predefined predictor to find the coefficient of each variable? why do you multiply prior scale by fraction of nonzero observations? when multiplying prior scale by fraction of observation, what is the problem? what is the difference between prior and nonzero why not multiply prior scale by fraction of nonzero predictor observations