如何在slidify
?
我的代码如下:
---
title : Another Introductory R Session
subtitle :
author : Christopher Meaney
job : Biostatistician, University of Toronto
framework : io2012 # {io2012, html5slides, shower, dzslides, ...}
highlighter : highlight.js # {highlight.js, prettify, highlight}
hitheme : tomorrow #
widgets : [mathjax] # {mathjax, quiz, bootstrap}
mode : selfcontained # {standalone, draft}
--- .nobackground
1. Item 1
2. Item 2
3. Item 3
4. Item 4
--- .nobackground
5. Create the following matrix `mat <- matrix(1:9,ncol=3)`.
* How many ways can you think of to get the column means of `mat`?
* Same idea with row means.
6. In matrix notation the OLS/MLE solution for the regression coeffiicients of a linear regression model can be expressed as:
$$ \hat{\boldsymbol\beta} = (\mathbf{X}^{\rm T}\mathbf{X})^{-1} \mathbf{X}^{\rm T}\mathbf{y} $$
* Using the cars dataset investigate the relationship between distance (response variable) as a function of speed (independent variable).
* Create the vector `y` and the design matrix `X`. Dont forget the leading column vector of 1's. Using all of R's fancy matrix algebra functions estimate the $\hat{\boldsymbol\beta}$ vector.
* Compare your matrix algebra approach with the following code: `lm(dist~speed,data=cars)`
我希望第二张幻灯片上的列表以5开头。第5项.6。第6项......依此类推。但是列表编号重置为1.项目5. 2.项目6等等。
答案 0 :(得分:2)
可能最简单的方法是在幻灯片内容后添加一些javascript:
--- .nobackground #foo
5. Create the following matrix `mat <- matrix(1:9,ncol=3)`.
* How many ways can you think of to get the column means of `mat`?
* Same idea with row means.
6. In matrix notation the OLS/MLE solution for the regression coeffiicients of a linear regression model can be expressed as:
$$ \hat{\boldsymbol\beta} = (\mathbf{X}^{\rm T}\mathbf{X})^{-1} \mathbf{X}^{\rm T}\mathbf{y} $$
* Using the cars dataset investigate the relationship between distance (response variable) as a function of speed (independent variable).
* Create the vector `y` and the design matrix `X`. Dont forget the leading column vector of 1's. Using all of R's fancy matrix algebra functions estimate the $\hat{\boldsymbol\beta}$ vector.
* Compare your matrix algebra approach with the following code: `lm(dist~speed,data=cars)`
<script>
$("#foo ol").attr('start', 5)
</script>
---
其他方法:
你可以使用html
---
<ol start="5">
<li>Item 5</li>
<li>Item 6</li>
</ol>
---
或者您可以使用CSS:
--- .nobackground #foo
5. Create the following matrix `mat <- matrix(1:9,ncol=3)`.
* How many ways can you think of to get the column means of `mat`?
* Same idea with row means.
6. In matrix notation the OLS/MLE solution for the regression coeffiicients of a linear regression model can be expressed as:
$$ \hat{\boldsymbol\beta} = (\mathbf{X}^{\rm T}\mathbf{X})^{-1} \mathbf{X}^{\rm T}\mathbf{y} $$
* Using the cars dataset investigate the relationship between distance (response variable) as a function of speed (independent variable).
* Create the vector `y` and the design matrix `X`. Dont forget the leading column vector of 1's. Using all of R's fancy matrix algebra functions estimate the $\hat{\boldsymbol\beta}$ vector.
* Compare your matrix algebra approach with the following code: `lm(dist~speed,data=cars)`
---
现在在您的assets / css中添加一个带有
的styles.css#foo OL {
counter-reset: item 4;
}
#foo OL>LI { display: block }
#foo OL>LI:before {
content: counter(item) ". ";
counter-increment: item;
display:block;
}
或者,您可以在幻灯片中将样式作为HTML插入
<style>
#foo OL {
counter-reset: item 4;
}
#foo OL>LI { display: block }
#foo OL>LI:before {
content: counter(item) ". ";
counter-increment: item;
display:block;
}
</style>