\HeaderA{notExp}{Functions for better-than-log positive parameterization}{notExp}
\aliasA{notLog}{notExp}{notLog}
\keyword{models}{notExp}
\keyword{smooth}{notExp}
\keyword{regression}{notExp}
\begin{Description}\relax
It is common practice in statistical optimization to use log-parameterizations when a 
parameter ought to be positive. i.e. if an optimization parameter \code{a} should be non-negative then 
we use \code{a=exp(b)} and optimize with respect to the unconstrained parameter \code{b}. This often works 
well, but it does imply a rather limited working range for \code{b}: using 8 byte doubles, for example, 
if \code{b}'s magnitude gets much above 700 then \code{a} overflows or underflows. This can cause 
problems for numerical optimization methods. 

\code{notExp} is a monotonic function for mapping the real line into the positive real line with much less
extreme underflow and overflow behaviour than \code{exp}. It is a piece-wise function, but is continuous 
to second derivative: see the source code for the exact definition, and the example below to see what it 
looks like.

\code{notLog} is the inverse function of \code{notExp}.

The major use of these functions is to provide more robust \code{pdMat} classes for \code{lme} for use by
\code{\LinkA{gamm}{gamm}}.
\end{Description}
\begin{Usage}
\begin{verbatim}
notExp(x)

notLog(x)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] Argument array of real numbers (\code{notExp}) or positive real numbers (\code{notLog}).
\end{ldescription}
\end{Arguments}
\begin{Value}
An array of function values evaluated at the supplied argument values.
\end{Value}
\begin{Author}\relax
Simon N. Wood \email{simon.wood@r-project.org}
\end{Author}
\begin{References}\relax
\url{http://www.stats.gla.ac.uk/~simon/}
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{pdTens}{pdTens}}, \code{\LinkA{pdIdnot}{pdIdnot}},  \code{\LinkA{gamm}{gamm}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Illustrate the notExp function: 
## less steep than exp, but still monotonic.
x <- -100:100/10
op <- par(mfrow=c(2,2))
plot(x,notExp(x),type="l")
lines(x,exp(x),col=2)
plot(x,log(notExp(x)),type="l")
lines(x,log(exp(x)),col=2) # redundancy intended
x <- x/4
plot(x,notExp(x),type="l")
lines(x,exp(x),col=2)
plot(x,log(notExp(x)),type="l")
lines(x,log(exp(x)),col=2) # redundancy intended
par(op)
range(notLog(notExp(x))-x) # show that inverse works!
\end{ExampleCode}
\end{Examples}

