summary.wb

Summarize information about a wb object.

manip

Computes Bayesian wavelet shrinkage credible intervals for
nonparametric regression.
The method uses cumulants to derive Bayesian credible intervals for
wavelet regression estimates.
The first four cumulants of the posterior distribution of the
estimates are expressed in terms of the observed data and integer
powers of the mother wavelet functions.
These powers are closely approximated by linear combinations of
wavelet scaling functions at an appropriate finer scale.
Hence, a suitable modification of the discrete wavelet transform allows
the posterior cumulants to be found efficiently for any data set.
Johnson transformations then yield the credible intervals themselves.
Barber, S., Nason, G.P. and Silverman, B.W. (2002)
<doi:10.1111/1467-9868.00332>.

Guy Nason

waveband

Computes Credible Intervals for Bayesian Wavelet Shrinkage

Stuart Barber

summary.wb function

<dl> <dt>object</dt>
<dd>wb object to summarize</dd> <dt>...</dt>
<dd>Other arguments (not used)</dd></dl>

Arguments

Author

Print information about a wb object. — summary.wb

<dl>

 <dt>object</dt>
<dd>wb object to summarize</dd>

 <dt>...</dt>
<dd>Other arguments (not used)</dd>

</dl>

summary.wb: Print information about a wb object.

Description

Usage

Value

Arguments

Author

Details

See Also

Examples