reverse.pwave

Reverse wavelet transform a set of probabilities in TItable
 format for Poisson data.

Fast, wavelet-based Empirical Bayes shrinkage methods for
signal denoising, including smoothing Poisson-distributed data and
Gaussian-distributed data with possibly heteroskedastic error. The
algorithms implement the methods described Z. Xing, P. Carbonetto &
M. Stephens (2021) <https://jmlr.org/papers/v22/19-042.html>.

Peter Carbonetto

smashr

Smoothing by Adaptive Shrinkage

Zhengrong Xing

Matthew Stephens

Kaiqian Zhang

Daniel Nachun

Guy Nason

Stuart Barber

Tim Downie

Piotr Frylewicz

Arne Kovac

Todd Ogden

Bernard Silverman

reverse.pwave function

<dl><dt>est</dt>
<dd>An n-vector. Usually a constant vector with each
element equal to the estimated log(total rate).</dd>
<dt>lp</dt>
<dd>A J by n matrix of probabilities.</dd>
<dt>lq</dt>
<dd>A J by n matrix of complementary probabilities.</dd></dl>

Arguments

Reverse wavelet transform a set of probabilities in TItable
  format for Poisson data. — reverse.pwave

<dl>

<dt>est</dt>
<dd>An n-vector. Usually a constant vector with each
element equal to the estimated log(total rate).</dd>


<dt>lp</dt>
<dd>A J by n matrix of probabilities.</dd>


<dt>lq</dt>
<dd>A J by n matrix of complementary probabilities.</dd>

</dl>

Reverse wavelet transform a set of probabilities in TItable
  format for Poisson data.

reverse.pwave: Reverse wavelet transform a set of probabilities in TItable format for Poisson data.

Description

Usage

Value

Arguments