Sentence examples for time series multiple from inspiring English sources

Treatment was introduced sequentially, across families, and evaluated in an interrupted time series, multiple baseline design.

As reference points for these time series, multiple replicates of untreated cells were sampled at time 0 (5 PBMC time zeros for the cytokine comparison, 4 PBMC time zeros for the dose response study, and 3 time zeros for each purified cell subset).

This is the relevant case for many practical examples where lags of multiple time series (multiple variables or observation functions) are required to achieve a mechanistic reconstruction of <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0018295.e211.PNG" class= inline-graphic"/> (e.g. [20]).

In brief, for a given time series, multiple "coarse-graining" time series are constructed by averaging the data points within nonoverlapping windows of increasing length τ, where τ represents the scale factor.

Given the single measured time series, multiple information is obtained by considering time delayed versions of the data (4) Y → (t ) = [ y (t ) y (t − τ ) ⋮ y (t − (m − 1 ) τ ) ], where τ is a time delay chosen in order that different functions in the vector Y → (t ) contain different information and the number m of elements of the vector is called the embedding dimension.

We use both multiple time points within a time series and multiple runs to capture the distribution both as might be observed over time within an aquaculture program and across independent runs.

In addition, we can also select multiple fields as targets, then the system will use time series of multiple topics to predict their future values.

The abnormality localization problem needs to consider the multiple EEG channels simultaneously since EEG data often come as correlated time series from multiple electrodes on the scalp.

A Fourier analysis of the temperature time series revealed multiple coherent oscillatory modes.

A program has been written in MATLAB for the integration of several time series from multiple sources.

Finally, the potential of the proposed methodology to simulate multivariate time series at multiple locations and incorporate climate change issues is discussed.