Test of Bookdown

Mads Stenbo Nielsen

2023-01-09

Kapitel 1 HTML formatting

Centered text

More centered text

The contents of the below subsections are located in a sub folder.

1.1 Basic text

This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)

##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

1.2 Including plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

link to subsection Basic text

1.3 Including images

knitr::include_graphics(normalizePath("../test_images/cbs_logo.png"))

Figure 1.1: This is CBS’ logo

This is section 1.3

See Figure 1.2.

Figure 1.2: The cars data.

Also see Equation (1.1).

$$\begin{equation} \bar{X} = \frac{\sum_{i=1}^n X_i}{n} \tag{1.1} \end{equation}$$

And see Table 1.1.

Table 1.1: The mtcars data.

	mpg	cyl	disp	hp	drat
Mazda RX4	21.0	6	160	110	3.90
Mazda RX4 Wag	21.0	6	160	110	3.90
Datsun 710	22.8	4	108	93	3.85
Hornet 4 Drive	21.4	6	258	110	3.08
Hornet Sportabout	18.7	8	360	175	3.15

Resultat: Transformation fra $N(\mu,\sigma)$ til $t$

1.4 Tip boxes

You use a div tip by writing ::: following by the name that you assigned to it in the CSS after the div.

1.5 Own boxes

Resultat: Fordeling af $\hat\mu$ (“my-hat”)

Lad $X_1,...,X_n$ være indbyrdes uafhængige observationer af en variabel, der er normalfordelt $N(\mu,\sigma)$. Vi estimerer normalfordelingens parametre ved $$\hat\mu=\frac{1}{n}\sum_{i=1}^nX_i\hspace{2cm}\hat\sigma=\sqrt{\frac{1}{n-1}\sum_{i=1}^n\left(X_i-\hat\mu\right)^2}$$ Estimatet af $\mu$ bliver selv normalfordelt $$\hat\mu\sim N\left(\mu,\frac{\sigma}{\sqrt{n}}\right)$$

Or we could do like this.

Another Definition

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or like this.

Another Definition

Praesent iaculis sed metus sed imperdiet. Nunc vitae augue bibendum, pulvinar neque id, suscipit justo. Quisque convallis, erat vel consectetur mattis, ante est euismod mauris, at condimentum enim erat id lorem. Phasellus volutpat id sapien a sollicitudin. Maecenas nec hendrerit felis.

Inserting animations

1.5.1 Example: gifski

Example: plotly

1.5.2 Example: gganimate

1.5.3 Example: gganimate (2nd try)

1.5.4 Example: gganimate (3rd try)

knitr::include_graphics(normalizePath("../test_subfolder/gdp_income_animation.gif"))