R: Inverse Haar-NN transform

invbinhf.wd {binhf} | R Documentation

## Inverse Haar-NN transform

### Description

Performs the inverse Haar-NN transform for binomial random variables.

### Usage

    invbinhf.wd(transformed, binsize = 1,print.info=FALSE)

### Arguments

`transformed` | a list of two components transformed: transformed observations of length a power of two and cnew: scaling coefficient vector used in Fisz modification.
`binsize` | the binomial size corresponding to the vector transformed.
`print.info` | boolean to print some information about the coefficients.

### Details

The procedure performs the Haar wavelet transform on the data transformed, and then modifies the wavelet coefficients by d'_jk=d_jk*sqrt(c_jk(N-c_jk)/2N). The inverse Haar transform is then performed. This modification will stabilize the variance of the resulting vector.

### Value

`estimate` | a vector of transformed observations corresponding to transformed.

### Note

This function requires the package wavethresh.

### Author(s)

Matt Nunes (m.nunes@ucl.ac.uk)

### References

Nunes, M.A. and Nason, G.P. (2009) “A Multiscale Variance Stabilization for binomial sequence proportion estimation", Statistica Sinica,19 (4), 1491–1510.

### See Also

`binhf.wd`

### Examples

    x<-rbinom(256,32,.35)

    y<-binhf.wd(x,32)

    x1<-invbinhf.wd(y,32)

[Package binhf version 1.0-1 Index]