\HeaderA{plot.confband.lines}{Adding Lines Satisfying a Confidence Criterion to the Current M
vs A Plot}{plot.confband.lines}
\keyword{aplot}{plot.confband.lines}
\begin{Description}\relax
This function adds 2 lines outlining the pointwise (intensity
dependent) confidence band on the M vs A plot.  The lines are drawn
such that a prespecified proportion of points are outside the 2
confidence curves.
The type of line may be specified as well as other parameters.
\end{Description}
\begin{Usage}
\begin{verbatim}
plot.confband.lines(x, M, crit1=0.025, crit2=crit1, nclass=10, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a vector giving the x-coordinates of the points in the scatter
plot. In the microarray context, this could be a vector of
average log intensities, ie A
\item[\code{M}] a vector giving the y-coordinates of the points in the scatter
plot. In the microarray context, this could be a vector of log
intensity ratios.
\item[\code{crit1}] The proportion of points less than the lower confidence
curve.  This takes a decimal value between 0 and 1. 
\item[\code{crit2}] The proportion of points greater than the upper confidence
curve.  By default, this has the same value as "crit1".
\item[\code{nclass}] A single number giving the approximate number of
intensity depedent groups to consider.
\item[\code{...}] graphical parameters may also be supplied as arguments
to the function (see  \code{\LinkA{par}{par}}).
\end{ldescription}
\end{Arguments}
\begin{Value}
Lines are added to the current plot.
\end{Value}
\begin{Note}\relax
An M vs A plot must be constructed \bold{prior} to the execution
of this function.
\end{Note}
\begin{SeeAlso}\relax
\code{\LinkA{plot.mva}{plot.mva}}, \code{\LinkA{stat.ma}{stat.ma}},
\code{\LinkA{lines}{lines}}, \code{\LinkA{matlines}{matlines}},
\code{\LinkA{plot.confband.text}{plot.confband.text}}, \code{\LinkA{plot.confband.points}{plot.confband.points}} .
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}data(MouseArray)
## mouse.setup <- init.grid
## mouse.data <- init.data

## To display an M vs A plot of the data 
plot.mva(mouse.data, mouse.setup) 

## Calculate M and A values 
mouse.lratio <- stat.ma(mouse.data, mouse.setup)

## To add default upper and lower confidence curves line to the M vs A plot
plot.confband.lines(mouse.lratio$A, mouse.lratio$M) 
\end{ExampleCode}
\end{Examples}

