%%visits: 5 So the variation and the amount of information we can get
from a parameter is dependant on the efficiency. The more variance, or
fisher_information, the less efficient the end variable is. ##
intuition== ## rigour== efficienc := $eff(\hat{\theta}_n) = \frac{1}{I_n(\theta)
var(\hat{\theta})}$
efficien := if eff(θ̂n)
= 1 then we say that the estimator is efficient.
assymptotically efficien := if limn → ∞eff(θ̂) = 1
then the estimator is asymptotically efficient.
[[Fisher_information]] [[variance]] {{file:../figures/screenshot_20211216_102027.png}} tags :math: