## The Interpolate, Truncate, Project (ITP) Root-Finding Algorithm

The itp package implements the Interpolate, Truncate, Project (ITP) root-finding algorithm of Oliveira and Takahashi (2021). Each iteration of the algorithm results in a bracketing interval for the root that is narrower than the previous interval. It’s performance compares favourably with existing methods on both well-behaved functions and ill-behaved functions while retaining the worst-case reliability of the bisection method. For details see the authors’ Kudos summary and the Wikipedia article ITP method.

### Examples

We use three examples from Section 3 of Oliveira and Takahashi (2021) to illustrate the use of the itp function. Each of these functions has a root in the interval (−1,1). The function can be supplied either as an R function or as an external pointer to a C++ function.

library(itp)

#### A continuous function

The Lambert function l(x) = xex − 1 is continuous.

The itp function finds an estimate of the root, that is, x* for which f(x*) is (approximately) equal to 0. The algorithm continues until the length of the interval that brackets the root is smaller than 2ϵ, where ϵ is a user-supplied tolerance. The default is ϵ = 10−10.

First, we supply an R function that evaluates the Lambert function.

# Lambert, using an R function
lambert <- function(x) x * exp(x) - 1
itp(lambert, c(-1, 1))
#> function: lambert
#>       root     f(root)  iterations
#>     0.5671   2.048e-12           8

Now, we create an external pointer to a C++ function that has been provided in the itp package and pass this pointer to the function itp(). For more information see the Overview of the itp package vignette.

# Lambert, using an external pointer to a C++ function
lambert_ptr <- xptr_create("lambert")
itp(lambert_ptr, c(-1, 1))
#> function: lambert_ptr
#>       root     f(root)  iterations
#>     0.5671   2.048e-12           8

#### The function itp_c

Also provided is the function itp_c, which is equivalent to itp, but the calculations are performed entirely using C++, and the arguments differ slightly: itp_c has a named required argument pars rather than ... and it does not have the arguments interval, f.a or f.b.

# Calling itp_c()
res <- itp_c(lambert_ptr, pars = list(), a = -1, b = 1)
res
#> function:
#>       root     f(root)  iterations
#>     0.5671   2.048e-12           8

#### A discontinuous function

The staircase function s(x) = ⌈10x − 1⌉ + 1/2 is discontinuous.

The itp function finds the discontinuity at x = 0 at which the sign of the function changes. The value of 0.5 returned for the root res$root is the midpoint of the bracketing interval [res$a, res$b] at convergence. # Staircase staircase <- function(x) ceiling(10 * x - 1) + 1 / 2 res <- itp(staircase, c(-1, 1)) print(res, all = TRUE) #> function: staircase #> root f(root) iterations a b f.a #> 7.404e-11 0.5 31 0 1.481e-10 -0.5 #> f.b precision #> 0.5 7.404e-11 #### A function with multiple roots The Warsaw function$w(x) = I(x > -1)\left(1 + \sin\left(\frac{1}{1+x}\right)\right)-1\$ has multiple roots.

When the initial interval is [−1,1] the itp function finds the root x ≈  − 0.6817. There are other roots that could be found from a different initial interval.

# Warsaw
warsaw <- function(x) ifelse(x > -1, sin(1 / (x + 1)), -1)
itp(warsaw, c(-1, 1))
#> function: warsaw
#>       root     f(root)  iterations
#>    -0.6817  -5.472e-11          11

### Installation

To get the current released version from CRAN:

install.packages("itp")

### Vignette

See the Overview of the itp package vignette, which can also be accessed using vignette("itp-vignette", package = "itp").