meta user
network profile
| bio | website | |
|---|---|---|
| location | Munich | |
| age | ||
| visits | member for | 1 year, 10 months |
| seen | May 13 at 20:03 | |
| stats | profile views | 151 |
|
Oct 31 |
accepted | Proof for convergence of a given progression $a_n := n^n / n!$ |
|
Oct 31 |
comment |
Proof for convergence of a given progression $a_n := n^n / n!$ Interesting approach, but the other hints were much easier to use. Sorry. |
|
Oct 31 |
asked | Proof for convergence of a given progression $a_n := n^n / n!$ |
|
Oct 9 |
accepted | Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT |
|
Oct 9 |
accepted | Function as parameter in Wolfram Mathematica |
|
Oct 8 |
comment |
Function as parameter in Wolfram Mathematica Is there any way, like in programming languages, to define an "anonymous function" (a.k.a. lambda-expression) the way i tried? |
|
Oct 8 |
comment |
Function as parameter in Wolfram Mathematica It does not work like expected! E.g. $E(f)(x)$ is now called TranslateEx. TranslateEx[fn_] := Apply[fn, {x + 1}] and then TranslateEx[x] leads to the result x[1 + x]. What does this mean? I expected x + 1 as the result. EDIT It seems i cannot enter a function directly and i need to specify it explicitly... |
|
Oct 8 |
asked | Function as parameter in Wolfram Mathematica |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT @cardinal: My ranges are sometimes different. It might happen, that i want to pick a number out of [1;20] and sometimes out of [1;100]. Which technique is used to compute the most convenient standard deviation because there are many numbers left out if i use a wide interval and $a=\sigma=1$. |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT @cardinal: I tried Box-Muller, however i was not able to shift the median like with Marsaglia! And if i think about the scenario: in the time i compute 1.000 uniform numbers i will need... 10 normal ones and i am confident, that i will be have with this :) |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT @Gortaur: I have a solution - please have a look at my question which is edited now. |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT @cardinal: Found the solution - look at my original question ;) |
|
Oct 2 |
revised |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT found solution! |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT @cardinal: I need this only 10 times at the beginning of the game and maybe in really special circumstances and therefore efficiency is not that important. ;) |
|
Oct 2 |
comment |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT I must confess, that adding a scalar $a$ was my first idea, however my algorithm seems buggy and it doesn't work like expected. Furthermore, debugging my code revealed that i am getting sometimes numbers $\leq 0$ which is weird. Any suggestions what i can do? |
|
Oct 2 |
revised |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT introduced algorithm |
|
Oct 2 |
revised |
Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT added 32 characters in body |
|
Oct 2 |
asked | Transform uniform distribution to normal distribution using Lindeberg–Lévy CLT |
|
Sep 17 |
comment |
Inductive proof for the Binomial Theorem for rising factorials Interesting way of prooving this, however i have to do this via induction. Still thanks for sharing the idea. |
|
Sep 16 |
accepted | Inductive proof for the Binomial Theorem for rising factorials |
