numeric vector, the x-points where data should be generated.
lambda
numeric, the mean signal magnitude.
sigma
numeric, the noise level.
x.delta
numeric, the minimum spacing allowed between spline knots. Defines background smoothness.
knots.n
numeric, a number of spline knots to generate.
peaks.widthRange
numeric vector, specifies range in peak widths.
peaks.n
numeric, the number of peaks to generate.
Details
The background is calculated as a sum of fundamental splines on the randomly generated knots. The function is a sum of the background, random peaks, and Gaussian noise.
Value
An object of type data (see set.data) with the following elements added:
knots
list with elements x and y that specify the knot positions and knot values, respectively.
bkg
numeric vector containing the generated background.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(BBEST)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/BBEST/test.signal.Rd_%03d_medium.png", width=480, height=480)
> ### Name: test.signal
> ### Title: A random function with a smooth background
> ### Aliases: test.signal
>
> ### ** Examples
>
> # 1. Create test function
> f <- test.signal(x=seq(0,30,0.01), lambda=5,
+ sigma=0.1, x.delta=1.0, knots.n=5,
+ peaks.widthRange=c(0.1, 0.3), peaks.n=7)
>
> # 2. Plot results
> plot(f$x, f$y, t="l", xlab="x", ylab="f")
> lines(f$x, f$bkg, col=2)
> lines(f$x, f$y - f$bkg, col="gray")
> legend(20, .9*max(f$y), c("test function", "background",
+ "peaks+noise"), lty=1, col=c(1,2,"gray"))
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.