\Header{uniroot}{One Dimensional Root (Zero) Finding}
\keyword{optimize}{uniroot}
\begin{Description}\relax
The function \code{uniroot} searches the interval from \code{lower}
to \code{upper} for a root (i.e., zero) of the function \code{f} with
respect to its first argument.
\end{Description}
\begin{Usage}
\begin{verbatim}
uniroot(f, interval, lower = min(interval), upper = max(interval),
        tol = .Machine$double.eps^0.25, maxiter = 1000, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{f}] the function for which the root is sought.
\item[\code{interval}] a vector containing the end-points of the interval
to be searched for the root.
\item[\code{lower}] the lower end point of the interval to be searched.
\item[\code{upper}] the upper end point of the interval to be searched.
\item[\code{tol}] the desired accuracy (convergence tolerance).
\item[\code{maxiter}] the maximum number of iterations.
\item[\code{...}] additional arguments to \code{f}.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
Either \code{interval} or both \code{lower} and \code{upper} must be
specified.  The function uses Fortran subroutine \file{"zeroin"} (from
Netlib) based on algorithms given in the reference below.

If the algorithm does not converge in \code{maxiter} steps, a warning
is printed and the current approximation is returned.
\end{Details}
\begin{Value}
A list with four components: \code{root} and \code{f.root} give the
location of the root and the value of the function evaluated at that
point. \code{iter} and \code{estim.prec} give the number of iterations
used and an approximate estimated precision for \code{root}.
\end{Value}
\begin{References}\relax
Brent, R. (1973)
\emph{Algorithms for Minimization without Derivatives.}
Englewood Cliffs, NJ: Prentice-Hall.
\end{References}
\begin{SeeAlso}\relax
\code{\Link{polyroot}} for all complex roots of a polynomial;
\code{\Link{optimize}}, \code{\Link{nlm}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
f <- function (x,a) x - a
str(xmin <- uniroot(f, c(0, 1), tol = 0.0001, a = 1/3))
str(uniroot(function(x) x*(x^2-1) + .5, low = -2, up = 2, tol = 0.0001),
    dig = 10)
str(uniroot(function(x) x*(x^2-1) + .5, low = -2, up =2 , tol = 1e-10 ),
    dig = 10)

## Find the smallest value x for which exp(x) > 0 (numerically):
r <- uniroot(function(x) 1e80*exp(x) -1e-300,,-1000,0, tol=1e-20)
str(r, digits= 15)##> around -745.1332191

exp(r$r)        # = 0, but not for r$r * 0.999...
minexp <- r$r * (1 - .Machine$double.eps)
exp(minexp)     # typically denormalized
\end{ExampleCode}
\end{Examples}

