Add Gaussian white noise to functional data objects
This function generates an artificial noisy version of a functional data
object of class funData (univariate) or
multiFunData (multivariate) by adding iid. realizations
of Gaussian random variables \eps ~ N(0, σ^2) to the observations. The standard deviation
σ can be supplied by the user.
addError(funDataObject, sd)
funDataObject |
A functional data object of class
|
sd |
The standard deviation σ of the Gaussian white noise
that is added to the data. Defaults to |
An object of the same class as funDataObject, which is a noisy
version of the original data.
oldPar <- par(no.readonly = TRUE)
set.seed(1)
# Univariate functional data
plain <- simFunData(argvals = seq(0,1,0.01), M = 10, eFunType = "Fourier",
eValType = "linear", N = 1)$simData
noisy <- addError(plain , sd = 0.5)
veryNoisy <- addError(plain, sd = 2)
plot(plain, main = "Add error", ylim = range(veryNoisy@X))
plot(noisy, type = "p", pch = 20, add = TRUE)
plot(veryNoisy, type = "p", pch = 4, add = TRUE)
legend("topright", c("Plain", "Noisy", "Very Noisy"), lty = c(1, NA, NA), pch = c(NA, 20 ,4))
# Multivariate functional data
plain <- simMultiFunData(type = "split", argvals = list(seq(0,1,0.01), seq(-.5,.5,0.02)), M = 10,
eFunType = "Fourier", eValType = "linear", N = 1)$simData
noisy <- addError(plain , sd = 0.5)
veryNoisy <- addError(plain, sd = 2)
par(mfrow = c(1,2))
plot(plain[[1]], main = "Add error (multivariate)", ylim = range(veryNoisy[[1]]@X))
plot(noisy[[1]], type = "p", pch = 20, add = TRUE)
plot(veryNoisy[[1]], type = "p", pch = 4, add = TRUE)
plot(plain[[2]], main = "Add error (multivariate)", ylim = range(veryNoisy[[2]]@X))
plot(noisy[[2]], type = "p", pch = 20, add = TRUE)
plot(veryNoisy[[2]], type = "p", pch = 4, add = TRUE)
legend("topright", c("Plain", "Noisy", "Very Noisy"), lty = c(1, NA, NA), pch = c(NA, 20 ,4))
par(oldPar)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.