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How would conformal map from $\Bbb C\backslash\{z\in\Bbb C : Im(z)=0, Re(z)\le 0\}$ to the unit disc $\{|z|<1\}$ look like?
Riemann's theorem guarantees the existence of a conformal mapping $f:\Omega\mapsto D$ where $\Omega=\Bbb C\backslash\{z\in\Bbb C : Im(z)=0, Re(z)\le 0\}$ is simply connecte...
In mathematics, a conformal map is a function that preserves orientation and angles locally. In the most common case, the function has a domain and an image in the complex plane.
More formally, let
U
{\displaystyle U}
and
V
{\displaystyle V}
be open subsets of
R
n
{\displaystyle \mathbb {R} ^{n}}
. A function
f
:
U
→
V
...
The umvue tag has one question on it. Do we want to keep it going or not?
For those of us who are not familiar with UMVUEs (uniformly minimum-variance unbiased estimators), the long story short is that they are (in my opinion) the culmination of a statistical inference course when it comes to p...2
I've started to learn methods of finding UMVUE distribution. I found some nice examples on this site.
I got stuck while evaluating UMVUE for Poisson distribution for a parametric function $g(\theta)$.
How did the author get
$$\sum_{t=o}^\infty \frac{h(t) n^t}{t!} \theta^t = e^{n \theta}g(\th...
In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.
For practical statistics problems, it is important to determine the MVUE if one exists, since less-than-optimal procedures would naturally be avoided, other things being equal. This has led to substantial development of statistical theory related to the problem of optimal estimation.
While combining the constraint of unbiasedness with the desirability metric...
