## 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:

ARG1-PPT:

ARG2-PPT:

*causer of 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 Julia#### Aliases:

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:

ARG1-PPT:

ARG2-PPT:

*agent/causer of correlation*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 Julia#### Aliases:

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:

ARG1-PPT:

ARG2-PPT:

*agent/causer of correlation*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

.