rmd-demo.Rmd

---
title: "A"
author: "Erick A. Chacon-Montalvan"
date: "05 Feb 2018"
documentclass: SimpleNotes
classoption: 11pt, a4paper, top=3.7cm, bottom=3.5cm, right=2.5cm, left=3cm
output:
  pdf_document:
    includes:
      in_header: rmd-header.tex
    template: rmd-template.tex
    number_sections: true
    fig_caption: true
---

<!-- geometry: top=4.7cm, bottom=3.5cm, right=2.5cm, left=3cm -->


# Introduction

In the geometric distribution, $\theta$ represents the probability of succes in each trial. Furthermore, it should follow that $y$ is countable and greater than one. In general, in the negative binomial distribution, $y$ is the number of trials until get the $k$ first success.
In the geometric distribution, $\theta$ represents the probability of succes in each trial. Furthermore, it should follow that $y$ is countable and greater than one. In general, in the negative binomial distribution, $y$ is the number of trials until get the $k$ first success.

- first
- another
- another
- another
    - another
    - another
    - another
    - another
- another
- another

\begin{sframe}{box_color}
  \textbf{Statement}:\\
\begin{equation}
  \label{eq:bla}
~~p(y>r|\theta)=(1-\theta)^r,
\end{equation}
where $r = 1,2,...$
\end{sframe}

\begin{sframe}{white}
\textbf{Proof}:
\[p(y>r|\theta)=1-p(y\leq r|\theta)\]

\[p(y>r|\theta)=1-\sum\limits_{k=1}^{r}(1-\theta)^{k-1}\theta\]

\[p(y>r|\theta)=1-\theta\sum\limits_{k=1}^{r}(1-\theta)^{k-1}\]
\[p(y>r|\theta)=1-\theta\bigg[\frac{1-(1-\theta)^r}{1-(1-\theta)}\bigg]\]
\[p(y>r|\theta)=1-\theta\bigg[\frac{1-(1-\theta)^r}{\theta}\bigg]\]
\[p(y>r|\theta)=1-[1-(1-\theta)^r]=(1-\theta)^r\fp\]
\end{sframe}

| Tables        | Are           | Cool  |
| ------------- |:-------------:| -----:|
| col 3 is      | right-aligned | $1600 |
| col 2 is      | centered      |   $12 |
| zebra stripes | are neat      |    $1 |

Table: Your Caption


```{r, echo = FALSE, fig.cap = "hla"}
library(ggplot2)
data <- data.frame(x = 1:10, y = 10:1)
ggplot(data, aes(x, y)) + geom_point()
```