turbotrend {TurboNorm} | R Documentation

## turbotrend: a fast scatterplot smoother

### Description

A fast scatterplot smoother based on B-splines with second order difference penalty

### Usage

    turbotrend(x, y, w = rep(1, length(y)), n = 100, lambda=10^seq(-10, 10, length=1000), iter=0, method=c("original", "demmler"))

### Arguments

`x,y` | vectors giving the coordinates of the points in the scatter plot.
`w` | vector of weights of with same length as the data for a weighted smoothing. Default all weights are 1.
`n` | an integer indicating the number of intervals equal to 1 + number of knots. Currently the intervals must be langer than 10.
`lambda` | Optionally a user-defined penalty parameter can be provided, if not generalized cross-validation is used to find the optimal penalty parameter.
`iter` | Number of robustifying iterations similar as lowess.
`method` | method for solving the system of linear equations either using the data in the original space or transformed to the Demmler-Reinsch basis.

### Details

some details about implementation

### Value

An object of type `pspline` is returned as a list with the following items:

`x` | original data vector x
`y` | fitted y-values with same length as vector x
`w` | vector of weights
`n` | number of bins
`ytrend` | binnend fitted y-values
`xtrend` | binned x-values
`lambda` | if scalar penalty parameter used else if vector of two lower and upper bound of the grid
`iter` | number of robustifying iterations
`gcv` | generalized cross-validation
`edf` | effective degrees of freedom (trace of the smoother matrix)
`call` | function call which produced this output

### Author(s)

Maarten van Iterson, Chantal van Leeuwen

### References

van Iterson M, Duijkers FA, Meijerink JP, Admiraal P, van Ommen GJ, Boer JM, van Noesel MM, Menezes RX (2012). A novel and fast normalization method for high-density arrays. SAGMB, 11(4).

Paul .H.C. Eilers and Brain D. Marx (1996). Flexible smoothing with B-splines and Penalties. Statistical Science, Vol 11, No. 2, 89-121.

### See Also

`loess`,`lowess`, `smooth`, `smooth.spline` and `smooth.Pspline`

### Examples

    library(marray)
    data(swirl)

    x <- maA(swirl)[,1]
    y <- maM(swirl)[,1]
    xord <- x[order(x)]
    yord <- y[order(x)]

    plot(xord, yord, main = "data(swirl)  &  smoothing splines + lowess")
    lines(turbotrend(xord, yord), col = "red", lwd=2)
    lines(smooth.spline(xord, yord), col = "green", lwd=2)
    lines(lowess(xord, yord), col = "purple", lwd=2)
    legend("topleft", c("piecewise constant P-splines", "Cubic B-splines", "lowess"), text.col=c("red","green","purple"), bty="n")

[Package TurboNorm version 1.36.0 Index]