Estimates standard deviation of noise

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Description

Estimates standard deviation of noise in the nonparametric signal+(Gaussian noise) regression model. Input vector must be of dyadic length and assumes a regular grid.

Usage

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scale(yobs, L=3, deg=3)

Arguments

yobs

a vector of dyadic length representing signal+(Gaussian noise)

L

lowest resolution level

deg

degree of Meyer wavelet

Value

Returns a positive estimate of the standard deviation of noise in the nonparametric regression model.

Author(s)

Marc Raimondo

References

Raimondo, M. and Stewart, M. (2006), ‘The WaveD Transform in R’, preprint, School and Mathematics and Statistics, University of Sydney.

See Also

WaveD

Examples

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library(waved)
data=waved.example(TRUE,FALSE)
scale(data$lidar.noisy)

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