correlate
correlate.01 - to be mutually related
CORRELATE-V NOTES: Frame created by Claire (from correlate.01-v)CORRELATION-N NOTES: correlate.01 (from correlation.01-n)
Aliases:
correlate (v.)
correlation (n.)
correlated (j.)
correlation (n.)
correlated (j.)
Roles:
ARG0-PAG: causer of relation
ARG1-PPT: topic, first entity in relation
ARG2-PPT: with what? second entity in relation
ARG1-PPT: topic, first entity in relation
ARG2-PPT: with what? second entity in relation
correlate-v: Linguist Favorite: sign and signified
In this restricted senseARGM-MNR
, signsARG1
are causallyARGM-MNR
correlatedrel
with that which is signifiedARG2
.correlation-n: All args, inanimate causer
The study 'sARG0
correlationrel
between cell phone usageARG1
and cancer ratesARG2
is tenuous at best .autocorrelate
autocorrelate.02 - cross-correlation of something (a signal?) with itself
AUTOCORRELATE-V NOTES: Added by JuliaAliases:
autocorrelate (v.)
auto-correlate (v.)
auto_correlate (v.)
autocorrelation (n.)
auto-correlation (n.)
auto_correlation (v.)
auto-correlate (v.)
auto_correlate (v.)
autocorrelation (n.)
auto-correlation (n.)
auto_correlation (v.)
Roles:
ARG0-PAG: agent/causer of correlation
ARG1-PPT: first (or all) instances correlated
ARG2-PPT: second instance correlated
ARG1-PPT: first (or all) instances correlated
ARG2-PPT: second instance correlated
autocorrelate-v
If a time series of length NARG1
is autocorrelatedrel
, the number of independent observations is fewer than N .autocorrelation-n
In statistics , the
autocorrelationrel
of a random processARG1
describes the correlation between values of the process at different times , as a function of the two times or of the time lag .crosscorrelate
crosscorrelate.03 - compare one set of data against another
CROSSCORRELATE-V NOTES: Added by JuliaAliases:
crosscorrelate (v.)
cross-correlate (v.)
cross_correlate (v.)
crosscorrelation (n.)
cross-correlation (n.)
cross_correlation (v.)
cross-correlate (v.)
cross_correlate (v.)
crosscorrelation (n.)
cross-correlation (n.)
cross_correlation (v.)
Roles:
ARG0-PAG: agent/causer of correlation
ARG1-PPT: first (or all) set correlated
ARG2-PPT: second set
ARG1-PPT: first (or all) set correlated
ARG2-PPT: second set
crosscorrelate-v
For each CMBR mapARGM-ADV
, weARG0
generated 5000 realizations and crossrel
-rel
correlatedrel
themARG1
against each of the four galaxy mapsARG2
.cross_correlation-m
One approach to identifying a pattern within an image uses
crossrel
correlationrel
of the imageARG1
with a suitable maskARG2
.