knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(calculus)
The function taylor
provides a convenient way to compute the Taylor series of arbitrary unidimensional or multidimensional functions. The mathematical function can be specified both as a character
string or as a function
. Symbolic or numerical methods are applied accordingly. For univariate functions, the $n$-th order Taylor approximation centered in $x_0$ is given by:
$$ f(x) \simeq \sum_{k=0}^n\frac{f^{(k)}(x_0)}{k!}(x-x_0)^k $$
where $f^{(k)}(x_0)$ denotes the $k$-th order derivative evaluated in $x_0$. By using multi-index notation, the Taylor series is generalized to multidimensional functions with an arbitrary number of variables:
$$ f(x) \simeq \sum_{|k|=0}^n\frac{f^{(k)}(x_0)}{k!}(x-x_0)^k $$
where now $x=(x_1,\dots,x_d)$ is the vector of variables, $k=(k_1,\dots,k_d)$ gives the order of differentiation with respect to each variable $f^{(k)}=\frac{\partial^{(|k|)}f}{\partial^{(k_1)}{x_1}\cdots \partial^{(k_d)}{x_d}}$, and:
$$|k| = k_1+\cdots+k_d \quad\quad k!=k_1!\cdots k_d! \quad\quad x^k=x_1^{k_1}\cdots x_d^{k_d}$$
The summation runs for $0\leq |k|\leq n$ and identifies the set
$${(k_1,\cdots,k_d):k_1+\cdots k_d \leq n}$$
that corresponds to the partitions of the integer $n$. These partitions can be computed with the function partitions
that is included in the package and optimized in C++
for speed and flexibility. For example, the following call generates the partitions needed for the $2$-nd order Taylor expansion for a function of $3$ variables:
partitions(n = 2, length = 3, fill = TRUE, perm = TRUE, equal = FALSE)
Based on these partitions, the function taylor
computes the corresponding derivatives and builds the Taylor series. The output is a list
containing the Taylor series, the order of the expansion, and a data.frame
containing the variables, coefficients and degrees of each term in the Taylor series.
taylor("exp(x)", var = "x", order = 2)
By default, the series is centered in $x_0=0$ but the function also supports $x_0\neq 0$, the multivariable case, and the approximation of user defined R functions
.
f <- function(x, y) log(y)*sin(x) taylor(f, var = c(x = 0, y = 1), order = 2)
Guidotti E (2022). “calculus: High-Dimensional Numerical and Symbolic Calculus in R.” Journal of Statistical Software, 104(5), 1-37. doi:10.18637/jss.v104.i05
A BibTeX entry for LaTeX users is
@Article{calculus, title = {{calculus}: High-Dimensional Numerical and Symbolic Calculus in {R}}, author = {Emanuele Guidotti}, journal = {Journal of Statistical Software}, year = {2022}, volume = {104}, number = {5}, pages = {1--37}, doi = {10.18637/jss.v104.i05}, }
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