| Name : R-VAR.spec
| |
| Version : 1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.2
| Date : 2024-06-14 11:04:28
|
| Group : Development/Libraries/Other
| Source RPM : R-VAR.spec-1.0-lp153.1.2.src.rpm
|
| Size : 0.12 MB
| |
| Packager : (none)
| |
| Summary : Allows Specifying a Bivariate VAR (Vector Autoregression) with Desired Spectral Characteristics
|
Description :
The spectral characteristics of a bivariate series (Marginal Spectra,
Coherency- and Phase-Spectrum) determine whether there is a strong
presence of short-, medium-, or long-term fluctuations (components of
certain frequencies in the spectral representation of the series) in
each one of them. These are induced by strong peaks of the marginal
spectra of each series at the corresponding frequencies. The spectral
characteristics also determine how strongly these short-, medium-, or
long-term fluctuations of the two series are correlated between the two
series. Information on this is provided by the Coherency spectrum at
the corresponding frequencies. Finally, certain fluctuations of the two
series may be lagged to each other. Information on this is provided by
the Phase spectrum at the corresponding frequencies. The idea in this
package is to define a VAR (Vector autoregression) model with desired
spectral characteristics by specifying a number of polynomials,
required to define the VAR. See Ioannidis(2007)
< doi:10.1016/j.jspi.2005.12.013>. These are specified via their roots,
instead of via their coefficients. This is an idea borrowed from the
Time Series Library of R. Dahlhaus, where it is used for defining ARMA
models for univariate time series. This way, one may e.g. specify a VAR
inducing a strong presence of long-term fluctuations in series 1 and in
series 2, which are weakly correlated, but lagged by a number of time
units to each other, while short-term fluctuations in series 1 and in
series 2, are strongly present only in one of the two series, while
they are strongly correlated to each other between the two series.
Simulation from such models allows studying the behavior of
data-analysis tools, such as estimation of the spectra, under different
circumstances, as e.g. peaks in the spectra, generating bias, induced
by leakage.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
