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.
I’m not sure if a g prior is what you mean by “informative prior”? If so, then the information you want is in this part of the docs for
|vector of responses
|number of simulations desired
|list with components
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 it’s assumed you will be reading the book where more explanation may be offered (I don’t know, I don’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 don’t even see the
prior parameter used — if a parameter has a default, you don’t have to specify it when calling the function unless you want something different from the default.
By inference (here’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 =
, beta0 =
with your desired values or calculations in the blanks.
I’m afraid I don’t quite know what you’re looking for here. Can you describe what you’re confused about in more detail, or give a small example?