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\documentclass{article}
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\documentclass{article}
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\usepackage{amsmath}
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\usepackage{amsmath}
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% -------- Umlaute korrekt ----------------
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\usepackage[utf8]{inputenc}
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\usepackage[ngerman, english]{babel}
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%-------------------------------------------
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% TikZ Library
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\usepackage{tikz}
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\usetikzlibrary{arrows,backgrounds,positioning,fit,calc,petri}
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\usetikzlibrary{shapes, shapes.misc}
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\usetikzlibrary{decorations.markings,decorations.pathmorphing}
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% -----------------------------------------
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\DeclareMathSizes{10}{10}{10}{10}
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\DeclareMathSizes{10}{10}{10}{10}
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\title{Mathe C4 Merz - Cheatsheet}
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\title{Mathe C4 Merz - Cheatsheet}
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\author{Yannik Schmidt (Sheppy)\\September 2015}
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\author{Yannik Schmidt (Sheppy)\\September 2015}
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% \\ \\ \textbf{Moeglichkeit b) - Nach $x_1$ oder $x_2$ umstellen} \\ (ggf. mit Koordinatentransformation)
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% \\ \\ \textbf{Moeglichkeit b) - Nach $x_1$ oder $x_2$ umstellen} \\ (ggf. mit Koordinatentransformation)
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\subsubsection{Alternatives Beispiel:}
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\subsubsection{Alternatives Beispiel:}
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X,Y stochastisch unabhaengige, mit Parameter 'p' geometrisch verteilte Zufallsvarriablen in Wahrscheinlichkeitsraum $(\varOmega , \mathcal{A},P)$. Welche Verteilung besitzt
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X,Y stochastisch unabhaengige, mit Parameter 'p' geometrisch verteilte Zufallsvarriablen in Wahrscheinlichkeitsraum $(\varOmega , \mathcal{A},P)$. Welche Verteilung besitzt
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Zufallsvarriable $Z = min(X,Y)$, definiert durch $Z( \omega ) = min \{X(\omega),Y(\omega)\}$.\\ \[
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Zufallsvarriable $Z = min(X,Y)$, definiert durch $Z( \omega ) = min \{X(\omega),Y(\omega)\}$.\\
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\]
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\section{Marginaldichte - Beispielrechnung}
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\section{Marginaldichte - Beispielrechnung}
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\[
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\[
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f(x_z,x_2)=
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f(x_z,x_2)=
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@ -264,23 +275,42 @@ und:
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\int \int f(x_1,x_2) dx_1 dx_2 = 1
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\int \int f(x_1,x_2) dx_1 dx_2 = 1
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\]
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\]
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\section{Koordinatentransformation}
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\section{Koordinatentransformation}
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\section{Komposition von Zufallsvektoren}
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\begin{center}
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\begin{tikzpicture}[
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bend angle=45,
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scale = 1.5,
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pre/.style={<-,shorten <=1pt,>=stealth',semithick},
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post/.style={->,shorten >=1pt,>=stealth',semithick},
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mid/.style={-,shorten >=1pt,>=stealth',semithick},
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place/.style={circle,draw=red!50,fill=red!20,thick}]
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\node[place] (A) at ( 0,0)[label=above:Before] {$(\Omega, A, P) $};
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\node[place] (B) at ( 2,0) {$(R^n, B_n, P^X)$}
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edge [pre] node [auto] {X} (A);
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\node[place, align=center] (C) at ( 2,-3) {$(R^m, B_m, P^G$}
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edge [pre] node [auto] {$Y = G \circ X$} (A)
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edge [pre] node [auto] {$G$} (B);
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\end{tikzpicture}
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\end{center}
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\vspace*{7pt}
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Problem: Verteilung von $P^G$ gesucht bei gegebenen $P^X$:
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\begin{enumerate}
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\item Funktionaldeterminante ($J_{G(x)}$) von $G$ berechnen
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\item Umkehrabbildung $G^*$ berechnen. Alle Zufallsvariablen werden
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werden mittels Funktionen verändert: z.B: $y_1 = x_1/x_2$.
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Jede i-te Funktion nach $x_i$ auflösen.
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\item Gesuchte Funktion: $g(y) = f(G^*(y))\frac{1}{|J_G(G^*(y))|}$\\
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$\longrightarrow$ Setze für alle $x_i$ dementsprechend $y_i$ ein und multipliziere
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mit Kehrwehrt von Funktionaldeterminante.
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\end{enumerate}
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\begin{align}
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J_{G(x)} =
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\begin{pmatrix}
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\frac{\partial G_1}{\partial x_1} (x) & \cdots & \frac{\partial G_1}{\partial x_n} (x) \\
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\vdots & \ddots & \vdots \\
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\frac{\partial G_n}{\partial x_1} (x) & \cdots & \frac{\partial G_n}{\partial x_n} (x) \\
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\end{pmatrix}
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\end{align}
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\end{document}
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\end{document}
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22
Public/m4/Makefile
Normal file
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Public/m4/Makefile
Normal file
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PDF = MaC4Cheatsheet
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all: $(PDF)
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continuous: $(PDF).continuous
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%.continuous: %.pdf
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latexmk -jobname=$(@:%.continuous=%) -pvc -pdf $(@:%.continuous=%).tex
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$(PDF): $(PDF).pdf
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%.pdf: %.tex
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latexmk -jobname=$(@:%.pdf=%) -pdf $<
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clean:
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latexmk -c -f $(PDF).tex
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distclean:
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latexmk -C -f $(PDF).tex
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rm -f $(PDF).pdf
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.PHONY: all clean distclean $(PDF) continuous
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