B Bookdown cheat sheet
# to see non-scientific notation a result
format(12e-17, scientific = FALSE)
#> [1] "0.00000000000000012"B.1 Operation
R commands for taking derivatives of a defined function involve the expression, D, and eval functions. You wrap the function you want to differentiate in expression(), apply D() to take the derivative, and use eval() to compute the result.
B.1.1 simple example
#define a function
f=expression(sqrt(x))
#take the first derivative
df.dx=D(f,'x')
df.dx
#> 0.5 * x^-0.5
#take the second derivative
d2f.dx2=D(D(f,'x'),'x')
d2f.dx2
#> 0.5 * (-0.5 * x^-1.5)B.2 Math Expression/ Syntax
B.2.1 Aligning equations
\[ \begin{aligned} a & = b \\ X &\sim {Norm}(10, 3) \\ 5 & \le 10 \end{aligned} \]
B.2.2 Cross-reference equation
\[\begin{equation} a = b \tag{B.1} \end{equation}\]to refer in a sentence (B.1) (\@ref(eq:test))
| Math Syntax | Notation |
|---|---|
$\pm$ |
\(\pm\) |
$\ge$ |
\(\ge\) |
$\le$ |
\(\le\) |
$\neq$ |
\(\neq\) |
$\equiv$ |
\(\equiv\) |
$^\circ$ |
\(^\circ\) |
$\times$ |
\(\times\) |
$\cdot$ |
\(\cdot\) |
$\leq$ |
\(\leq\) |
$\geq$ |
\(\geq\) |
\propto |
\(\propto\) |
$\subset$ |
\(\subset\) |
$\subseteq$ |
\(\subseteq\) |
$\leftarrow$ |
\(\leftarrow\) |
$\rightarrow$ |
\(\rightarrow\) |
$\Leftarrow$ |
\(\Leftarrow\) |
$\Rightarrow$ |
\(\Rightarrow\) |
$\approx$ |
\(\approx\) |
$\mathbb{R}$ |
\(\mathbb{R}\) |
$\sum_{n=1}^{10} n^2$ |
\(\sum_{n=1}^{10} n^2\) |
$$\sum_{n=1}^{10} n^2$$ |
\[\sum_{n=1}^{10} n^2\] |
$x^{n}$ |
\(x^{n}\) |
$x_{n}$ |
\(x_{n}\) |
$\overline{x}$ |
\(\overline{x}\) |
$\hat{x}$ |
\(\hat{x}\) |
$\tilde{x}$ |
\(\tilde{x}\) |
\check{} |
\(\check{}\) |
\underset{\gamma}{\operatorname{argmin}} |
\(\underset{\gamma}{\operatorname{argmin}}\) |
$\frac{a}{b}$ |
\(\frac{a}{b}\) |
$\frac{a}{b}$ |
\(\frac{a}{b}\) |
$\displaystyle \frac{a}{b}$ |
\(\displaystyle \frac{a}{b}\) |
$\binom{n}{k}$ |
\(\binom{n}{k}\) |
$x_{1} + x_{2} + \cdots + x_{n}$ |
\(x_{1} + x_{2} + \cdots + x_{n}\) |
$x_{1}, x_{2}, \dots, x_{n}$ |
\(x_{1}, x_{2}, \dots, x_{n}\) |
\mathbf{x} = \langle x_{1}, x_{2}, \dots, x_{n}\rangle$ |
\(\mathbf{x} = \langle x_{1}, x_{2}, \dots, x_{n}\rangle\) |
$x \in A$ |
\(x \in A\) |
$|A|$ |
\(|A|\) |
$x \in A$ |
\(x \in A\) |
$x \subset B$ |
\(x \subset B\) |
$x \subseteq B$ |
\(x \subseteq B\) |
$A \cup B$ |
\(A \cup B\) |
$A \cap B$ |
\(A \cap B\) |
$X \sim Binom(n, \pi)$ |
\(X \sim Binom(n, \pi)\) |
$\mathrm{P}(X \le x) = \text{pbinom}(x, n, \pi)$ |
\(\mathrm{P}(X \le x) = \text{pbinom}(x, n, \pi)\) |
$P(A \mid B)$ |
\(P(A \mid B)\) |
$\mathrm{P}(A \mid B)$ |
\(\mathrm{P}(A \mid B)\) |
$\{1, 2, 3\}$ |
\(\{1, 2, 3\}\) |
$\sin(x)$ |
\(\sin(x)\) |
$\log(x)$ |
\(\log(x)\) |
$\int_{a}^{b}$ |
\(\int_{a}^{b}\) |
$\left(\int_{a}^{b} f(x) \; dx\right)$ |
\(\left(\int_{a}^{b} f(x) \; dx\right)\) |
$\left[\int_{\-infty}^{\infty} f(x) \; dx\right]$ |
\(\left[\int_{-\infty}^{\infty} f(x) \; dx\right]\) |
$\left. F(x) \right|_{a}^{b}$ |
\(\left. F(x) \right|_{a}^{b}\) |
$\sum_{x = a}^{b} f(x)$ |
\(\sum_{x = a}^{b} f(x)\) |
$\prod_{x = a}^{b} f(x)$ |
\(\prod_{x = a}^{b} f(x)\) |
$\lim_{x \to \infty} f(x)$ |
\(\lim_{x \to \infty} f(x)\) |
$\displaystyle \lim_{x \to \infty} f(x)$ |
\(\displaystyle \lim_{x \to \infty} f(x)\) |
| Greek Letters | |
$\alpha A$ |
\(\alpha A\) |
$\beta B$ |
\(\beta B\) |
$\gamma \Gamma$ |
\(\gamma \Gamma\) |
$\delta \Delta$ |
\(\delta \Delta\) |
$\epsilon \varepsilon E$ |
\(\epsilon \varepsilon E\) |
$\zeta Z \sigma $ |
\(\zeta Z \sigma\) |
$\eta H$ |
\(\eta H\) |
$\theta \vartheta \Theta$ |
\(\theta \vartheta \Theta\) |
$\iota I$ |
\(\iota I\) |
$\kappa K$ |
\(\kappa K\) |
$\lambda \Lambda$ |
\(\lambda \Lambda\) |
$\mu M$ |
\(\mu M\) |
$\nu N$ |
\(\nu N\) |
$\xi\Xi$ |
\(\xi\Xi\) |
$o O$ |
\(o O\) |
$\pi \Pi$ |
\(\pi \Pi\) |
$\rho\varrho P$ |
\(\rho\varrho P\) |
$\sigma \Sigma$ |
\(\sigma \Sigma\) |
$\tau T$ |
\(\tau T\) |
$\upsilon \Upsilon$ |
\(\upsilon \Upsilon\) |
$\phi \varphi \Phi$ |
\(\phi \varphi \Phi\) |
$\chi X$ |
\(\chi X\) |
$\psi \Psi$ |
\(\psi \Psi\) |
$\omega \Omega$ |
\(\omega \Omega\) |
$\cdot$ |
\(\cdot\) |
$\cdots$ |
\(\cdots\) |
$\ddots$ |
\(\ddots\) |
$\ldots$ |
\(\ldots\) |
Limit P(\lim_{n\to \infty}\bar{X}_n =\mu) =1
\[ P(\lim_{n\to \infty}\bar{X}_n =\mu) =1 \]
Matrices
\[ \begin{array} {rrr} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{array} \]
\[ \mathbf{X} = \left[\begin{array} {rrr} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{array}\right] \]
Aligning Equations
Aligning Equations with Comments
\begin{aligned}
3+x &=4 && \text{(Solve for} x \text{.)}\\
x &=4-3 && \text{(Subtract 3 from both sides.)}\\
x &=1 && \text{(Yielding the solution.)}
\end{aligned}\[ \begin{aligned} 3+x &=4 & &\text{(Solve for} x \text{.)} \\ x &=4-3 && \text{(Subtract 3 from both sides.)} \\ x &=1 && \text{(Yielding the solution.)} \end{aligned} \]
B.2.3 Statistics Notation
$$
f(y|N,p) = \frac{N!}{y!(N-y)!}\cdot p^y \cdot (1-p)^{N-y} = \binom{N}{y} \cdot p^y \cdot (1-p)^{N-y}
$$\[ f(y|N,p) = \frac{N!}{y!(N-y)!}\cdot p^y \cdot (1-p)^{N-y} = \binom{N}{y} \cdot p^y \cdot (1-p)^{N-y} \]
\[ \begin{cases} \frac{1}{b-a} & \text{for } x\in[a,b]\\ 0 & \text{otherwise}\\ \end{cases} \]
B.3 Table
+---------------+---------------+--------------------+
| Fruit | Price | Advantages |
+===============+===============+====================+
| *Bananas* | $1.34 | - built-in wrapper |
| | | - bright color |
+---------------+---------------+--------------------+
| Oranges | $2.10 | - cures scurvy |
| | | - **tasty** |
+---------------+---------------+--------------------+| Fruit | Price | Advantages |
|---|---|---|
| Bananas | $1.34 |
|
| Oranges | $2.10 |
|
\((\mathbf{x}^T\mathbf{x})^{-1}\mathbf{x}^T\mathbf{y}\)