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  \code{\link{scatter.smooth}} adds a \code{\link{loess}}
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  \code{\link{scatter.smooth}} adds a \code{\link{loess}}
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  regression smoother to a scatter plot.
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  regression smoother to a scatter plot.
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}
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}
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\author{Florian Hahne at FHCRC, originally}
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\author{Florian Hahne at FHCRC, originally}
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\examples{
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\examples{
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  ## A largish data set
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## A largish data set
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  n <- 10000
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n <- 10000
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  x1  <- matrix(rnorm(n), ncol = 2)
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x1  <- matrix(rnorm(n), ncol = 2)
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  x2  <- matrix(rnorm(n, mean = 3, sd = 1.5), ncol = 2)
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x2  <- matrix(rnorm(n, mean = 3, sd = 1.5), ncol = 2)
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  x   <- rbind(x1,x2)
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x   <- rbind(x1, x2)
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  oldpar <- par(mfrow = c(2,2))
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oldpar <- par(mfrow = c(2, 2))
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  smoothScatter(x, nrpoints = 0)
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smoothScatter(x, nrpoints = 0)
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  smoothScatter(x)
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smoothScatter(x)
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  ## a different color scheme:
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## a different color scheme:
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  Lab.palette <-
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      colorRampPalette(c("blue", "orange", "red"), space = "Lab")
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Lab.palette <- colorRampPalette(c("blue", "orange", "red"), space = "Lab")
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  smoothScatter(x, colramp = Lab.palette)
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smoothScatter(x, colramp = Lab.palette)
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  ## somewhat similar, using identical smoothing computations,
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## somewhat similar, using identical smoothing computations,
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  ## but considerably *less* efficient for really large data:
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## but considerably *less* efficient for really large data:
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  plot(x, col = densCols(x), pch = 20)
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plot(x, col = densCols(x), pch = 20)
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  ## use with pairs:
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## use with pairs:
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  par(mfrow = c(1,1))
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par(mfrow = c(1, 1))
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  y <- matrix(rnorm(40000), ncol = 4) + 3*rnorm(10000)
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y <- matrix(rnorm(40000), ncol = 4) + 3*rnorm(10000)
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  y[, c(2,4)] <-  -y[, c(2,4)]
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y[, c(2,4)] <-  -y[, c(2,4)]
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  pairs(y, panel = function(...) smoothScatter(..., nrpoints = 0, add = TRUE))
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pairs(y, panel = function(...) smoothScatter(..., nrpoints = 0, add = TRUE))
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  par(oldpar)
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par(oldpar)
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}
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}
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\keyword{hplot}
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\keyword{hplot}