acf.bspec | R Documentation |
Deriving (posterior) autocovariances or autocorrelations from the spectrum's posterior distribution.
## S3 method for class 'bspec' acf(x, spec = NULL, type = c("covariance", "correlation"), two.sided = x$two.sided, ...)
x |
a |
spec |
(optional) a |
type |
a |
two.sided |
a |
... |
currently unused. |
If spec
is supplied, the autocovariance (or autocorrelation)
function corresponding to that specific spectrum will be returned.
As this is a completely deterministic relationship, the
“stderr
” slot of the result will be zero in this case.
If spec
is not supplied, the (posterior) expected
autocovariance is returned in the “acf
” element, and its
(posterior) standard deviation is returned in the
“stderr
” element.
The posterior expectation of the autocovariance is only finite if
all (!) posterior degrees-of-freedom parameters in the
bspec
object are >2. The posterior
variance (and with that the stderr
element) is only finite if all
these are >4.
Autocorrelations are only returned if spec
is supplied.
A list of class bspecACF
containing the following components:
lag |
a |
acf |
a |
stderr |
a |
type |
a |
N |
an |
bspec |
a |
(Posterior) expectation and standard deviation of the spectrum may in
many cases not be finite (see above).
Autocorrelations are only returned if spec
is supplied.
Christian Roever, christian.roever@med.uni-goettingen.de
Roever, C., Meyer, R., Christensen, N. Modelling coloured residual noise in gravitational-wave signal processing. Classical and Quantum Gravity, 28(1):015010, 2011. doi: 10.1088/0264-9381/28/1/015010. See also arXiv preprint 0804.3853.
bspec
,
expectation
,
sample.bspec
,
acf
lhspec1 <- bspec(lh) # without any prior specifications, # autocovariances are not finite: print(acf(lhspec1)) str(acf(lhspec1)) # for given values of the spectral parameters, # the autocovariances are fixed: str(acf(lhspec1, spec=sample(lhspec1))) # for all the prior degrees-of-freedom greater than one, # the expected autocovariance is finite, its variance isn't: lhspec2 <- bspec(lh, priordf=2, priorscale=0.6, intercept=FALSE) print(acf(lhspec2)) str(acf(lhspec2)) plot(acf(lhspec2))
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