I#8217;ve been trying to figure out how to use Markov Chain Monte
Carlo for Bayesian analysis and there is (at least) one aspect that
I#8217;m not getting. Basically, I#8217;m not sure how variances are
optimized.
To use a simple example (for which an analytic solution exists),
let#8217;s use a
Greetings!
I have one Y and two Xs (X1 and X2), and am trying to perform multiple
linear regression. All Xs and Y variables are standardized (zero mean
and unit variance). X1 and X2 are moderately correlated (r=0.6) and
the correlation of X1 and X2 to Y is -0.2 and 0.3, respectively.
ANOVA
On 23 Jan 2002 07:52:49 -0800, [EMAIL PROTECTED] (Mike Granaas) wrote:
[ snip ]
... Their
goal was then to test whether the pattern of endorsements was indeed
# item 1 # item 2 # item 3 # item 4 # item 5
where # item 1 is short
That is the most amusing post I have seen here in quite a while. Thanks,
Steven.
PS -- I have a virtual snippet of Steven Lee's hair and a voodoo doll in his
likeness. All those $50 payments should be wired to me or Steven will find
himself having sharp pains with no apparent cause. ;-)
-
Hi
On 23 Jan 2002, Sangdon Lee wrote:
I have one Y and two Xs (X1 and X2), and am trying to perform multiple
linear regression. All Xs and Y variables are standardized (zero mean
and unit variance). X1 and X2 are moderately correlated (r=0.6) and
the correlation of X1 and X2 to Y is -0.2
