Sentence examples for standard autocorrelation from inspiring English sources

Unlike the standard autocorrelation method, this improved analysis produces a plot that converges to the background count rate, instead of following an exponential decay.

We analysed the data from Experiment 2 using both the standard autocorrelation across trials (Pearson) and the Spearman rank-method across trial segments, and found quite high correlations at the first lag in all data (typically >0.25), with strong correlations continuing in the rotating walker data for several additional lags.

Fluorescence fluctuations were evaluated with standard autocorrelation analysis within the Zeiss AIM 4.2 software.

Since the suggested method is currently limited to isotropic Brownian diffusion described by single rotational correlation time, it is considered at this stage as a complementary approach to the standard autocorrelation methods.

Several statistical indices (within-person variance or standard deviation, autocorrelation …) have been used and several definitions have been formulated.

Then the variation of the Kendall tau coefficient as a function of the distance between genes was measured with a standard linear autocorrelation function [ 15, 16] (see methods and figure 1 part 3).

The results favor oscillatory long run autocorrelations over standard long run autocorrelation filters to model the log daily return range.

The analysis of the frequency variation under a fuel starvation condition was done using RMSF (root mean square frequency) and ACSD (autocorrelation standard deviation).

In this step, a "cap-fitting" algorithm is used to automatically detect a spike free segment and then the mean, standard deviation and autocorrelation function of the noise are computed.

Following Avdagic and Salardi (2013) and Nickell et al. (2005), we opt for a generalized least squares (GLS) model, while allowing for panel-level heteroscedastic standard errors and autocorrelation of the first order.

For other application areas, features can look completely different, as for example summarised in Lemke et al. (2009) for the area of time series forecasting, where features can include, for example, length, seasonality, autocorrelation, standard deviation and trends of the series.