\documentclass[crop,tikz]{standalone} \usepackage{amsmath} \usetikzlibrary{arrows.meta, positioning} \begin{document} \begin{tikzpicture}[ dist/.style = {draw, rectangle, align=center, rounded corners}, limit/.style = {dashed}, >={Stealth[round,sep]} ] \node [align=left] at (3, -17.5) { Solid lines represent transformations and special cases\\ Dashed lines represent limits\\ \footnotesize Adapted from Casella + Berger (1990) }; \node[dist] (Geometric) at (0,0) { \textbf{Geometric}\\ $(p)$ }; \node[dist] (DiscreteUniform) at (6,0) { \textbf{Discrete Uniform} }; \node[dist] (NegativeBinomial) at (2,-2) { \textbf{Negative binomial}\\ $(n, p)$ }; \node[dist] (Poisson) at (2,-4) { \textbf{Poisson}\\ $(\lambda)$ }; \node[dist] (BetaBinomial) at (6,-2) { \textbf{Beta-binomial}\\ $(n,\alpha,\beta)$ }; \node[dist] (Binomial) at (6,-4) { \textbf{Binomial}\\ $(n,p)$ }; \node[dist] (Hypergeometric) at (10,-2) { \textbf{Hypergeometric}\\ $(M, N, K)$ }; \node[dist] (Bernoulli) at (10,-5) { \textbf{Bernoulli}\\ $(p)$ }; \node[dist] (Normal) at (4, -6) { \textbf{Normal}\\ $(\mu, \sigma^{2})$ }; \node[dist] (Lognormal) at (0, -6.5) {\textbf{Lognormal}}; \node[dist] (Beta) at (8, -7.5) { \textbf{Beta}\\ $(\alpha, \beta)$ }; \node[dist] (Gamma) at (5.5, -9) { \textbf{Gamma}\\ $(r, \lambda)$ }; \node[dist] (Uniform) at (9, -10) {\textbf{Uniform}}; \node[dist] (ChiSquared) at (4, -11) { \textbf{Chi-Squared}\\ $(v)$ }; \node[dist] (NormalU) at (1, -8.5) { \textbf{Normal}\\ $(0,1)$ }; \node[dist] (Cauchy) at (0, -11) {\textbf{Cauchy}}; \node[dist] (Exponential) at (7.5, -13) { \textbf{Exponential}\\ $(\lambda)$ }; \node[dist] (Weibull) at (5, -16) { \textbf{Weibull}\\ $(\gamma, \lambda)$ }; \node[dist] (Dexponential) at (10, -16) {\textbf{Double exponential}}; \node[dist] (F) at (3.5, -13.5) { \textbf{F}\\ $(v_{1}, v_{2})$ }; \node[dist] (T) at (1, -15) { \textbf{t}\\ $(v)$ }; \draw[->] (Geometric) to [loop above] node {$\min X_{i}$} (Geometric); \draw[->] (NegativeBinomial) to [bend right] node[right] {$n = 1$} (Geometric); \draw[->] (Geometric) to [bend right] node[left] {$\Sigma X_{i}$} (NegativeBinomial); \draw[->] (BetaBinomial) to node[left] {$\alpha=\beta=1$} (DiscreteUniform); \draw[->, limit] (NegativeBinomial) to node[left, align=right] { $\lambda=n(1 - p)$\\ $n \to \infty$ } (Poisson); \draw[->] (Poisson) to [loop left] node {$\Sigma X_{i}$} (Poisson); \draw[->,limit] (Binomial) to node[above, align=center] { $\lambda=np$\\ $n \to \infty$ } (Poisson); \draw[->,limit] (BetaBinomial) to node[right, align=left] { $p=\frac{\alpha}{\alpha+\beta}$\\ $\alpha+\beta \to \infty$ } (Binomial); \draw[->,limit] (Hypergeometric) to [bend left=15] node[right=20pt, align=left] { $p = \frac{M}{N}$\\ $n = K$\\ $N \to \infty$ } (Binomial); \draw[->] (Bernoulli) to node[above right] {$\Sigma X_{i}$} (Binomial); \draw[->] (Binomial) to [bend right=20] node[near end, below] {$n = 1$} (Bernoulli); \draw[->,limit] (Poisson) to node[left=10pt, align=right] { $\lambda=\sigma^{2}$\\ $\lambda \to \infty$ } (Normal); \draw[->,limit] (Binomial) to node[near end, right=12pt, align=left] { $\mu=np$\\ $\sigma^{2}=np(1-p)$\\ $n \to \infty$ } (Normal); \draw[->] (Normal) to [bend right=10] node[above] {$e^{x}$} (Lognormal); \draw[->] (Lognormal) to [bend right=10] node[below] {$\log X$} (Normal); \draw[->] (Normal) to [loop below] node[below] {$\Sigma X_{i}$} (Normal); \draw[->] (Lognormal) to [loop above] node {$\Pi X_{i}$} (Lognormal); \draw[->, limit] (Beta) to node [near end, right=12pt] {$\alpha=\beta \to \infty$} (Normal); \draw[->] (Gamma) to node [below right] {$\frac{X_{1}}{X_{1} + X_{2}}$} (Beta); \draw[->, limit] (Gamma) to node [right=6pt, align=left] { $\mu=r\lambda$\\ $\sigma^{2}=r\lambda^{2}$\\ $r\to\infty$ } (Normal); \draw[->] (Normal) to node [left] {$\frac{X-\mu}{\sigma}$} (NormalU); \draw[->] (NormalU) to [bend right=20] node [below=10pt] {$\mu + \sigma X$} (Normal); \draw[->] (NormalU) to node [left] {$\frac{X_{1}}{X_{2}}$} (Cauchy); \draw[->] (Cauchy) to [loop left] node [left] {$\frac{1}{X}$} (Cauchy); \draw[->] (Cauchy) to [out=100, in=150, looseness=8] node [above] {$\Sigma X_{i}$} (Cauchy); \draw[->] (NormalU) to node [near start, above right] {$\Sigma X_{i}^{2}$} (ChiSquared); \draw[->] (ChiSquared) to [loop left, looseness=2] node [above left] {$\Sigma X_{i}$} (ChiSquared); \draw[->] (Gamma) to node [above left, align=right] { $r = \frac{v}{2}$\\ $\lambda=2$ } (ChiSquared); \draw[->] (Beta) to [bend left] node [right] {$\alpha=\beta=1$} (Uniform); \draw[->] (Uniform) to [bend left=10] node [right] {$-\lambda \log X$} (Exponential); \draw[->] (Exponential) to [bend left=10] node [near end, left] {$e^{-x\lambda}$} (Uniform); \draw[->] (Exponential) to [bend right] node [near end, right] {$\Sigma X_{i}$} (Gamma); \draw[->] (Gamma) to node [left] {$r=1$} (Exponential); \draw[<->] (ChiSquared) to node [below=8pt, align=center] { $\lambda=2$\\ $v=2$ } (Exponential); \draw[->] (ChiSquared) to [bend right] node [left] {$\frac{X_{1}/ v_{1}}{X_{2}/ v_{2}}$} (F); \draw[->,limit] (F) to node [right, align=left] { $v_{1}X$\\ $v_{2} \to\infty$ } (ChiSquared); \draw[->] (Exponential) to [out=190, in=210, looseness=5] node [left] {$\min X_{i}$} (Exponential); \draw[->] (Exponential) to node [left] {$X^{\frac{1}{\gamma}}$} (Weibull); \draw[->] (Weibull) to [bend right=20] node [right] {$\gamma=1$} (Exponential); \draw[->] (Dexponential) to node [left] {$\lvert X\rvert$} (Exponential); \draw[->] (Exponential) to [bend left=20] node [right] {$X_{1}-X_{2}$} (Dexponential); \draw[->,limit] (T) to [bend right=5] node [near start, right] {$v\to\infty$} (NormalU); \draw[->] (T) to node [left] {$v=1$} (Cauchy); \draw[->] (T) to node [above] {$X^{2}$} (F); \end{tikzpicture} \end{document} %%% Local Variables: %%% mode: latex %%% TeX-master: t %%% End: