Sentence examples for between the data series from inspiring English sources

The lower diagram presents the difference between the data series.

The comparison between the data series and the models shows that both describe the data reasonably well, but neither the global nor the regional model captures the amplitude of most of the rapid SV changes.

Comparison of the rates measured for WT, E46K, and A53T αS reveals minimal differences between the data series, signifying nearly identical association rates for these variants (plots not shown, but rates summarized in Table 2).

This functional form represents the researchers' assumptions about the likely effects of the event, and the serial dependence between the function and the data series (in the form of auto-correlation functions) is used to estimate by how much the effect lagged the event.

The data series suggest that patterns of decline in mortality, and maternal mortality in particular, differ between countries.

Coefficients of determination (R) were calculated between the complete data series of δN and each of the other sedimentary proxies (total percent carbon, echinenone, zeaxanthin, and Mo/Al) (n = 194).

To ensure consistency between the two data series, a baseline value of 1 in 1996 is assumed for the IGC.

Squared coherence between the two data series are found as a function of T. For all three cases, we find that the squared coherency for daily variations, and all periods smaller than this, is relatively low, while the squared coherency for periods longer than two days is above 0.9.

Globally, the nonlinear ANN model approach is shown to provide a better prediction of daily average ammonia concentration than linear multiple regression and univariate time series analysis when the correlation between data series is low and when the models were obligated to predict in a situation for which specifically had not been calibrated.

In all these cases, a near-zero phase-lag relation between different data series is observed, reflecting the millisecond or even sub-millisecond precision required for feature integration [1], [7] [9].

The cross-correlation allows us to identify the proper temporal order of the covariates, since cross-correlations capture the degree of co-movement between data series across time.