Performs one-dimensional root-finding using the ITP algorithm of
Oliveira and Takahashi (2021). This function is equivalent to
`itp`

but 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`

.

`itp_c(f, pars, a, b, epsilon = 1e-10, k1 = -1, k2 = 2, n0 = 1)`

## Arguments

- f
An external pointer to a C++ function that evaluates the function
\(f\).

- pars
A list of additional arguments to the function. This may be an
empty list.

- a, b
Numeric scalars. Lower (`a`

) and upper `b`

limits of
the interval to be searched for a root.

- epsilon
A positive numeric scalar. The desired accuracy of the root.
The algorithm continues until the width of the bracketing interval for the
root is less than or equal to `2 * epsilon`

.

- k1, k2, n0
Numeric scalars. The values of the tuning parameters
\(\kappa\)_{1},
\(\kappa\)_{2},
\(n\)_{0}.
See the **Details** section of `itp`

.

The default value for `k1`

in `itp_c`

is set as
the inadmissible value of `-1`

(in reality \(\kappa\)_{1}
must be positive) as a device to set the same default value for `k1`

as `itp`

, that is, `k1 = 0.2 / (b - a)`

. If the input
value of `k1`

is less than or equal to 0 then, inside
`itp_c`

, `k1 = 0.2 / (b - a)`

is set.

## Value

An object (a list) of class `"itp"`

with the same structure
as detailed in the **Value** section of `itp`

, except
that the attribute `f_name`

is empty (equal to `""`

).

## Details

For details see `itp`

.

## References

Oliveira, I. F. D. and Takahashi, R. H. C. (2021). An Enhancement
of the Bisection Method Average Performance Preserving Minmax Optimality,
*ACM Transactions on Mathematical Software*, **47**(1), 1-24.
doi:10.1145/3423597

## See also

`print.itp`

and `plot.itp`

for print and
plot methods for objects of class `"itp"`

returned from `itp_c`

or `itp`

.

## Examples

```
wiki_ptr <- xptr_create("wiki")
wres <- itp_c(f = wiki_ptr, pars = list(), a = 1, b = 2, epsilon = 0.0005)
wres
#> function:
#> root f(root) iterations
#> 1.521 0.0001315 4
plot(wres, main = "Wiki")
```