Bayesian Variable Selection in Normal Regression Models
... An important task in building regression models is to decide which variables should be included into the model. In the Bayesian approach variable selection is usually accomplished by MCMC methods with spike and slab priors on the effects subject to selection. In this work different versions of spike ...
... An important task in building regression models is to decide which variables should be included into the model. In the Bayesian approach variable selection is usually accomplished by MCMC methods with spike and slab priors on the effects subject to selection. In this work different versions of spike ...
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... – For each value of x, the y’s are normally distributed with mean μy|x and standard deviation σy|x – μy|x = α + βx – Homoscedasticity – the standard deviation of y at each value of X is constant; σy|x the same for all values of X • The opposite of homoscedasticity is heteroscedasticity • This is sim ...
... – For each value of x, the y’s are normally distributed with mean μy|x and standard deviation σy|x – μy|x = α + βx – Homoscedasticity – the standard deviation of y at each value of X is constant; σy|x the same for all values of X • The opposite of homoscedasticity is heteroscedasticity • This is sim ...
