Abscissa and ordinate of the points on the scatterplot.
span
Specifies the amount of smoothing; span is the fraction
of points used to compute each fitted value; as span increases the
output becomes smoother.
NoXP
Another way of specifying the amount of smoothing; NoXP
is the Number of X Points used to compute each fitted value; it must
be larger than 3.
maxit
The number of iterations in the robust fit; if
maxit=c(0,0), the nonrobust fit is returned; the first entry
specifies the number of iterations using an asymmetric biweight
function, whereas the second entry specifies the number of
iterations using the usual (symmetric) biweight function.
b
Tuning constant in the biweight function.
weight
Optional weights to be given to individual
observations.
Scale
function specifying how to calculate the scale of the
residuals.
delta
Nonnegative parameter which may be used to save
computation. By default, if length(x) <= 100, delta is
set equal to 0; if length(x) > 100 set to 1/100th of the
range of x.
SORT
Boolean variable indicating whether x data must be
sorted. Change it only when the x are sorted and you want to safe
computer time.
DOT
If TRUE disregard outliers totally; that is, observations
with weight 0 are disregarded even when the neighbourhood is
determined.
init
Values of an initial fit.
Value
List containing components
x
Sorted input vector x with duplicate points removed
y
Corresponding input vector y
fit
Fitted values at x
rw
Robust weights of (x,y)-Points used in last iteration of fit
scale
Scale used in last iteration of fit
Author(s)
Andreas Ruckstuhl
References
Ruckstuhl, Andreas F., Matthew P. Jacobson, Robert W. Field and James
A. Dodd (2001); Baseline Subtraction Using Robust Local Regression
Estimation; Journal of Quantitative Spectroscopy and Radiative
Transfer 68: 179 – 193
Ruckstuhl, Andreas F., et al.; Estimation of background concentrations
of atmospheric trace gases using robust local regression; to be
published
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(IDPmisc)
Loading required package: grid
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/IDPmisc/rfbaseline.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rfbaseline
> ### Title: Robust Fitting of Baselines
> ### Aliases: rfbaseline
> ### Keywords: robust regression smooth
>
> ### ** Examples
>
> data(MS)
> MS1 <- log10(MS[MS$mz>12000&MS$mz<1e5,])
>
> MS1.rfb2 <- rfbaseline(x=MS1$mz, y=MS1$I, NoXP=2200, maxit=c(5,0))
> plot(x=MS1$mz, y=MS1$I, type="l",
+ xlab="log(mass/charge)", ylab="log(intensity)")
> lines(MS1.rfb2$x, MS1.rfb2$fit, col="orange", lwd=3)
>
> MS1.rfb3 <- rfbaseline(x=MS1$mz, y=MS1$I, NoXP=1100, maxit=c(5,0),
+ DOT=TRUE, Scale=function(x) mad(x, center=0))
> plot(x=MS1$mz, y=MS1$I, type="l",
+ xlab="log(mass/charge)", ylab="log(intensity)")
> lines(MS1.rfb3$x, MS1.rfb3$fit, col="orange", lwd=3)
>
> ## 'delta=0' needs much more computer time
> ## Not run:
> ##D MS1.rfb4 <- rfbaseline(x=MS1$mz, y=MS1$I, NoXP=2200,
> ##D delta=0, maxit=c(5,0))
> ##D plot(x=MS1$mz, y=MS1$I,ty="l",
> ##D xlab="log(mass/charge)", ylab="log(intensity)")
> ##D lines(MS1.rfb4$x, MS1.rfb4$fit, col="orange", lwd=3)
> ## End(Not run)
>
>
>
>
>
> dev.off()
null device
1
>