The documentation for blinreg()
says that it:
Gives a simulated sample from the joint posterior distribution of the regression vector and the error standard deviation for a linear regression model with a noninformative or g prior.
Iâ€™m not sure if a g prior is what you mean by â€śinformative priorâ€ť? If so, then the information you want is in this part of the docs for blinreg()
:
Usage
blinreg(y,X,m,prior=NULL)
Arguments


y 
vector of responses 
X 
design matrix 
m 
number of simulations desired 
prior 
list with components c0 and beta0 of Zellner's g prior 
Reading this sort of documentation takes some getting used to, and this is a particularly terse example. That may be because this is a book companion package, and itâ€™s assumed you will be reading the book where more explanation may be offered (I donâ€™t know, I donâ€™t have a copy of that book at hand).
But putting together the two sections above, we can see that the default for the prior
parameter is NULL
. This is why in basic examples, you donâ€™t even see the prior
parameter used â€” if a parameter has a default, you donâ€™t have to specify it when calling the function unless you want something different from the default.
By inference (hereâ€™s where the docs could be clearer!), prior = NULL
corresponds to an uninformative prior. To call blinreg()
with a g prior, we need to follow the instructions above and provide a list with certain named components as the prior
parameter, like:
prior = list(c0 =
Â , beta0 =
Â )
with your desired values or calculations in the blanks.
Iâ€™m afraid I donâ€™t quite know what youâ€™re looking for here. Can you describe what youâ€™re confused about in more detail, or give a small example?