-
sample mean is a
commonly used
estimator of the po****tion mean.
There are
point and
interval estimators. The
point estimators yield single-valued results...
- (notably in
shrinkage estimators); or
because in some
cases being unbiased is too
strong a condition, and the only
unbiased estimators are not useful. Bias...
- )} ****sky's
theorem can be used to
combine several different estimators, or an
estimator with a non-random
convergent sequence. If Tn →dα, and Sn →pβ...
- {X}},} an
estimator (estimation rule) δ M {\displaystyle \delta ^{M}\,\!} is
called minimax if its
maximal risk is
minimal among all
estimators of θ {\displaystyle...
-
estimator (in the
class of
unbiased estimators) if it
reaches the
lower bound in the Cramér–Rao
inequality above, for all θ ∈ Θ.
Efficient estimators...
- be
contrasted with a
distribution estimator.
Examples are
given by
confidence distributions,
randomized estimators, and
Bayesian posteriors. “Bias” is...
- In statistics, M-
estimators are a
broad class of
extremum estimators for
which the
objective function is a
sample average. Both non-linear
least squares...
- }}} . An
estimator θ ^ {\displaystyle {\widehat {\theta }}} is said to be a
Bayes estimator if it
minimizes the
Bayes risk
among all
estimators. Equivalently...
- what
estimators should be used
according to
those approaches. For example,
ideas from
Bayesian inference would lead
directly to
Bayesian estimators. Similarly...
-
unbiased estimators are used. The
theorem seems very weak: it says only that the Rao–Blackwell
estimator is no
worse than the
original estimator. In practice...
