regression

Examples of regressing

regressing

In English, many past and present participles of verbs can be used as adjectives. Some of these examples may show the adjective use.

In order to test this hypothesis, we divided our analysis into two parts, regressing political variables against inflation rates for the 1970s and 1980s separately.
Regressing to models of decaying exponentials led to improved quality in the synthesis of several of the percussive tracks.
He removed any residual seasonality from the real money growth rate by regressing it against seasonal dummies.
Table 1 does this by regressing total household income on the number of persons of different categories living in the household.
The serial correlation coefficients are estimated by regressing residuals on their lagged values and a constant term.
We have also included in the diagrams the correlations obtained from regressing the experimental data to a form as introduced by (2) and (6).
Apparent rates of disease increase were obtained by regressing transformed disease data against time.
Regressing one such series on another could give the appearance of a strong correlation despite the relationship being spurious.
This conclusion is based in part on the results of regressing threat perceptions on all seven evaluations.
Standardization equations were calculated by regressing the local results of panel testing in these countries against those of the reference laboratory.
However, there are several regressing dark cells that present different morphological alterations characteristic of the apoptotic process.
The investment-abatement relationship is obtained by regressing the annualized investment against the annual carbon savings.
Therefore, regressing current fertility rates on current values of the explanatory variables, as we have done above, may not give an accurate picture.
Country-specific standardization equations were calculated by regressing the local results of panel testing against those of the reference laboratory.
The adopted procedure involves regressing a time series on itself (an autoregression), using lagged values from the time series as predictors.
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