Monash Beamer Class Demonstration

In binb: 'binb' is not 'Beamer'

knitr::opts_chunk$set(echo = FALSE, message=FALSE, warning=FALSE, cache=TRUE, dev.args=list(bg=grey(0.9), pointsize=11))

Intro

Slide with bullets

• Bullet 1
• Bullet 2
• Bullet 3

Use \alert to \alert{highlight} some text

Some enumeration

1. The first item
2. Stuff
3. Nonsense

Using R

Slide with R output

summary(cars)

Slide with graphics

plot(pressure)

Slide with mathematics

Quantile score for observation $y$. For $0<p<1$:

\begin{block}{} [ S(y_t,q_t(p)) = \left{ \begin{array}{rl} p(y_t-q_t(p)) & \text{if $y_t \ge q_t(p)$}\ (1-p)(q_t(p)-y_t) & \text{if $y_t < q_t(p)$} \end{array}\right. ] \end{block}

Average score over all percentiles gives the best distribution forecast: [ QS = \frac{1}{99T}\sum_{p=1}^{99}\sum_{t=1}^T S(q_t(p),y_t) ]

RMarkdown Examples

R Figure

The following code generates the plot on the next slide (taken from help(bxp) and modified slightly):

\small

library(stats)
set.seed(753)
bx.p <- boxplot(split(rt(100, 4),
                      gl(5, 20)), plot=FALSE)
bxp(bx.p, notch = FALSE, boxfill = "orange",
    frame = FALSE, outl = TRUE,
    main = "Example from help(bxp)")

R Figure

library(stats)
set.seed(753)
bx.p <- boxplot(split(rt(100, 4),
                      gl(5, 20)), plot=FALSE)
bxp(bx.p, notch = FALSE, boxfill = "orange",
    frame = FALSE, outl = TRUE,
    main = "Example from help(bxp)")

R Table

A simple knitr::kable example:

\small

knitr::kable(mtcars[1:4, 1:7],
       caption="(Parts of) the mtcars dataset")

Resources

For more information:

• See the RMarkdown repository for more on RMarkdown
• See the binb repository for more on binb
• See the binb vignettes for more examples.

binb documentation built on July 2, 2020, 4:08 a.m.