wpstREGR

The <code>makewpstRO</code> function takes two time series,
performs a nondecimated wavelet packet transform with the "dependent"
variable one, stores the "best" packets (those that individually correlate
with the response series) and returns the data frame that contains the
response and the best packets. The idea is that the user then performs
some kind of modelling between response and packets. This function takes
a new "dependent" series and returns the best packets in a new data frame
in the same format as the old one. The idea is that the model and the new
data frame can be used together to predict new values for the response

multivariate

Performs 1, 2 and 3D real and complex-valued wavelet transforms,
nondecimated transforms, wavelet packet transforms, nondecimated
wavelet packet transforms, multiple wavelet transforms,
complex-valued wavelet transforms, wavelet shrinkage for
various kinds of data, locally stationary wavelet time series,
nonstationary multiscale transfer function modeling, density
estimation.

Guy Nason

wavethresh

Wavelets Statistics and Transforms

Stuart Barber

Tim Downie

Piotr Frylewicz

Arne Kovac

Todd Ogden

Bernard Silverman

wpstREGR function

<dl> <dt>newTS</dt>
<dd>The new "dependent" time series</dd> <dt>wpstRO</dt>
<dd>The previously constructed wpstRO object made by
	<code>makewpstRO</code></dd></dl>

Arguments

Author

Construct data frame using new time series using information
	from a previously constructed wpstRO object — wpstREGR

<dl>

 <dt>newTS</dt>
<dd>The new "dependent" time series</dd>

 <dt>wpstRO</dt>
<dd>The previously constructed wpstRO object made by
	<code>makewpstRO</code></dd>

</dl>

Construct data frame using new time series using information
	from a previously constructed wpstRO object

wpstREGR: Construct data frame using new time series using information from a previously constructed wpstRO object

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples