Spec_compare_fixed_freq {ftsspec} | R Documentation |
Test if two spectral density operators at some fixed frequency are equal.
Description
A test for the null hypothesis that two spectral density operators (at the
same frequency \omega
) are equal, using a pseudo-AIC criterion for the
choice of the truncation parameter. (used in
Spec_compare_localize_freq
)
Usage
Spec_compare_fixed_freq(spec1, spec2, is.pi.multiple, m, kappa.square,
autok = 2, K.fixed = NA)
Arguments
spec1 , spec2 |
The two sample spectral densities (at the same frequency |
is.pi.multiple |
A logical variable, to specify if |
m |
The number of Fourier frequencies over which the periodogram operator was smoothed. |
kappa.square |
the L2-norm of the weight function used to estimate the spectral density operator |
autok |
A variable used to specify if (and which) pseudo-AIC criterion
is used to select the truncation parameter |
K.fixed |
The value of K used if |
References
Tavakoli, Shahin and Panaretos, Victor M. "Detecting and Localizing Differences in Functional Time Series Dynamics: A Case Study in Molecular Biophysics", 2014, under revision
Panaretos, Victor M., David Kraus, and John H. Maddocks. "Second-order comparison of Gaussian random functions and the geometry of DNA minicircles." Journal of the American Statistical Association 105.490 (2010): 670-682.
See Also
Examples
ma.scale2=ma.scale1=c(-1.4,2.3,-2)
ma.scale2[3] = ma.scale1[3]+.3
a1=Generate_filterMA(10, 10, MA.len=3, ma.scale=ma.scale1)
a2=Generate_filterMA(10, 10, MA.len=3, ma.scale=ma.scale2)
X=Simulate_new_MA(a1, T.len=512, noise.type='wiener')
Y=Simulate_new_MA(a2, T.len=512, noise.type='wiener')
spec.X = Spec(X)
spec.Y = Spec(Y)
Spec_compare_fixed_freq(spec.X$spec[1,,], spec.Y$spec[1,,],
is.pi.multiple=TRUE, spec.X$m, spec.X$kappa.square)