computeDisc | R Documentation |
The dimension of cf$cf
and cf$icf
must be dim(Time, S, N)
,
where Time
is the time extent, S
is the number of samples and
N
the number of measurements (gauges). cf2
is the same, but
needed only for cross-correlators.
computeDisc(cf, cf2, real = TRUE, real2 = TRUE, smeared = FALSE, smeared2 = FALSE, subtract.vev = TRUE, subtract.vev2 = TRUE, subtract.equal = TRUE, use.samples, use.samples2, type = "cosh", verbose = FALSE)
cf |
loop data as produced by |
cf2 |
second set of loop data as produced by |
real |
use the real part |
real2 |
use the real part |
smeared |
use the loops instead of the local ones for |
smeared2 |
use the loops instead of the local ones for |
subtract.vev |
subtract a vacuum expectation value. It will be estimated as mean over all samples, gauges and times available. |
subtract.vev2 |
subtract a vacuum expectation value for the second set of loops. It will be estimated as mean over all samples, gauges and times available. |
subtract.equal |
subtract contributions of products computed on identical samples. This will introduce a bias, if set to FALSE for missing cf2 or if cf and cf2 are computed on the same set of random sources. |
use.samples |
If set to an integer, only the specified number of
samples will be used for |
use.samples2 |
Same like |
type |
The correlation function can either be symmetric or
anti-symmetric in time. Anti-symmetric is of course only possible for
cross-correlators. In this case with |
verbose |
Print some debug output, like the VEVs of the loops. |
If subtract.vev=TRUE
the vev is estimated as the mean over all
gauges, samples and times available and subtracted from the original loop
data. (Same for subtrac.vev2
.
The correlation is computed such as to avoid correlation between equal
samples, unless nrSamples
is equal to 1.
cf
and cf2
must agree in Time
, number of gauges and number
of samples. Matching of gauges is assumed. If this is not the case results
are wrong.
Returns an object of type cf
derived from a list
with
elements cf
, an array of dimension dim(N, Time)
, where N
is the number of samples and Time
the time extent, integers Time
for the time extent, nrStypes
and nrObs
for the available
smearing types and operators, and finally nrSamples
, the number of
samples used to generate the correlation function cf
.
Carsten Urbach, curbach@gmx.de
readcmidisc
, readbinarydisc
,
bootstrap.cf
, add.cf
, c.cf
data(loopdata) Cpi0v4 <- computeDisc(cf=loopdata, real=TRUE, subtract.vev=TRUE) Cpi0v4 <- bootstrap.cf(Cpi0v4, boot.R=99, boot.l=1, seed=14556)
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