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@ajtulloch
Created May 22, 2014 21:39
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\begin{comment}
#+ORGTBL: SEND Conjugates orgtbl-to-latex :splice nil :skip 0 :no-escape t
|----------------------+---------------------------------+-------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------+--------------------------------------------------------------------|
| L | P | ConjP | Posterior | Predictive |
|----------------------+---------------------------------+-------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------+--------------------------------------------------------------------|
| \textsc{Binomial} | $\theta$ | $\textsc{Beta}(a, b)$ | $a + y$, $b + n - y$ | $\textsc{BetaBinomial}(y)$ |
| \textsc{Poisson} | $\theta$ | $\textsc{Gamma}(a, b)$ | $a + y$, $b + n$ | $\textsc{NegativeBinomial}(y)$ |
| \textsc{Normal} | $\mu$ | $\textsc{Normal}(\gamma, \frac{\sigma^{2}}{n_{0}})$ | $\frac{n_{0} \gamma + n \overline y}{n_0 + n}, \sigma^{2}_{n} = \frac{\sigma^{2}}{n_{0} + n}$ | $\textsc{Normal}(\gamma_{n}, \sigma^{2} + \sigma^{2}_{n})$ |
| \textsc{Normal} | $\mu$ | $\textsc{Normal}(\gamma, \tau_{0})$ (precision) | $\frac{\tau_{0} \gamma + n \overline y}{\tau_{0} + n \tau}, \tau_{n} = \tau_{0} + n \tau$ | $\textsc{Normal}(\gamma_{n}, \frac{1}{\tau_{n}} + \frac{1}{\tau})$ |
| \textsc{Normal} | $\sigma^{2} = \frac{1}{\omega}$ | $\omega \sim \textsc{Gamma}(\frac{n_{0}}{2}, \frac{n_{0} \sigma_{0}^{2}}{2})$ | $\frac{n_{0} + n}{2}, \frac{n_{0} \sigma_{0}^{2}}{2} + \frac{1}{2} \sum (y_{i} - \mu)^{2}$ | |
| \textsc{Multinomial} | $p_{1}, \dots, p_{k}$ | $\textsc{Dirichlet}(\alpha_{1}, \dots, \alpha_{k})$ | $\alpha_{1} + n_{1}, \dots, \alpha_{k} + n_{k}$ | |
|----------------------+---------------------------------+-------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------+--------------------------------------------------------------------|
\end{comment}
\begin{comment}
#+ORGTBL: SEND Distributions orgtbl-to-latex :splice nil :skip 0 :no-escape t
|-----------------------------------------------------+------------------------------------------------------------------------------+------------------------------------------+-----------------------------------|
| Distribution | Density | Mean | Variance |
|-----------------------------------------------------+------------------------------------------------------------------------------+------------------------------------------+-----------------------------------|
| $\textsc{Normal}(\mu, \sigma^{2})$ | $\frac{1}{\sqrt{2 \pi \sigma^{2}}} exp(-\frac{(x - \mu)^{2}}{2 \sigma^{2}})$ | $\mu$ | $\sigma^{2}$ |
| $\textsc{Poisson}(\lambda)$ | $\frac{e^{-\lambda} \lambda^{k}}{k!}$ | $\lambda$ | $\lambda$ |
| $\textsc{Gamma}(a, b)$ | $\frac{b^{a}}{\Gamma(a)} x^{a-1} e^{-bx}$ | $\frac{a}{b}$ | $\frac{a}{b^{2}}$ |
| $\textsc{Beta}(a, b)$ | $\frac{\Gamma(a + b)}{\Gamma(a) \Gamma(b)} x^{a-1}(1-x)^{b-1}$ | $\frac{a}{a+b}$ | $\frac{ab}{(a+b)^{2}(a + b + 1)}$ |
| $\textsc{Dirichlet}(\alpha_{1}, \dots, \alpha_{K})$ | $\propto \prod_{i=1}^{K} x_{i}^{\alpha_{i} - 1}$ | $\frac{\alpha_{i}}{\sum_{k} \alpha_{k}}$ | |
|-----------------------------------------------------+------------------------------------------------------------------------------+------------------------------------------+-----------------------------------|
\end{comment}
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