On Sun, Dec 6, 2009 at 9:21 AM, <josef.p...@gmail.com> wrote: > On Sun, Dec 6, 2009 at 11:01 AM, Colin J. Williams <c...@ncf.ca> wrote: > > >
<snip> > What's the best estimate? That's the main question > > Estimators differ in their (sample or posterior) distribution, > especially bias and variance. > Stein estimator dominates OLS in the mean squared error, so although > it is biased, the variance of the estimator is smaller than OLS so that > MSE (bias plus variance) is also smaller for Stein estimator than for OLS. > Depending on the application there could be many possible loss functions, > including asymmetric, eg. if its more costly to over than to under > estimate. > > The following was a good book for this, that I read a long time ago: > Statistical decision theory and Bayesian analysis By James O. Berger > > > http://books.google.ca/books?id=oY_x7dE15_AC&pg=PP1&lpg=PP1&dq=berger+decision&source=bl&ots=wzL3ocu5_9&sig=lGm5VevPtnFW570mgeqJklASalU&hl=en&ei=P9cbS5CSCIqllAf-0f3xCQ&sa=X&oi=book_result&ct=result&resnum=4&ved=0CBcQ6AEwAw#v=onepage&q=&f=false > > At last, an explanation I can understand. Thanks Josef. Chuck
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
