848 reputation
822
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location Munich
age
visits member for 3 years, 2 months
seen Aug 17 at 14:22

Aug
23
revised Dimensions of symmetric and skew-symmetric matrices
added 45 characters in body; edited title
Aug
23
asked Dimensions of symmetric and skew-symmetric matrices
Aug
8
accepted Computation of $\mathbb{E}[\min(U+W,V+W)]$
Aug
7
revised Computation of $\mathbb{E}[\min(U+W,V+W)]$
added 104 characters in body
Aug
7
asked Computation of $\mathbb{E}[\min(U+W,V+W)]$
Jul
12
accepted $\chi^2$ test and sampling variance
Jul
10
revised Intuitionistic logic
corrected latex
Jul
10
suggested suggested edit on Intuitionistic logic
Jul
10
awarded  Critic
Jul
10
asked $\chi^2$ test and sampling variance
Jul
8
accepted Transformation of double-integral with $y-x\leq 1$ and $x-y\leq 1$ for probabilities
Jul
7
accepted Maximum-likelihood estimation for continuous random variable with unknown parameter
Jul
7
comment Maximum-likelihood estimation for continuous random variable with unknown parameter
Now it looks comprehensible. Thanks for reviewing this.
Jul
7
comment Maximum-likelihood estimation for continuous random variable with unknown parameter
Sorry, but in the first equation I still cannot see why the $x_j$ from $(2\lambda x_j)$ disappeared (assuming your $\chi$ is my $\textbf 1_A(x)$). I still get a $\left(\prod\limits_{j=1}^nx_j\right)$ term left to be multiplied with the rest.
Jul
7
comment Maximum-likelihood estimation for continuous random variable with unknown parameter
Did i miss something? I thought that $\|x\|=\sqrt{\sum\limits_{j=1}^nx_j^2}$.
Jul
7
comment Maximum-likelihood estimation for continuous random variable with unknown parameter
I have issues following your transformation to the exp function. And could you explain how you define your norm $\|x\|$?
Jul
7
revised Maximum-likelihood estimation for continuous random variable with unknown parameter
added 27 characters in body
Jul
7
asked Maximum-likelihood estimation for continuous random variable with unknown parameter
Jul
2
awarded  Yearling
Jun
25
comment Induction for sum of Poisson distributed random variables
Oh yep, so close... but it works!