"time series characteristics" is correct and usable in written English
You can use it to refer to the features and patterns in data collected over time. For example, "By analyzing the time series characteristics of stock prices, the analyst was able to make an accurate prediction of the market's future performance."
Having examined the time series characteristics of our data, in the next step, Eqs.
It is important to investigate the time series characteristics of the variables.
In-depth analysis of EDR time series characteristics requires data integrity tests, which check the EDR feature data for completeness and correctness.
In order to improve the accuracy of the temperature estimates, this paper proposes to take into account RASS time series characteristics.
First, filtering works best identifying time series characteristics when assuming a stationary process, even if the underlying process contains a unit root.
An exponential smoothing forecasting model was established based on the time series characteristics of the heavy metal pollution in the agricultural producing area to predict heavy metal pollution.
The time-series characteristics, including heat transfer characteristics and condensation modes, were experimentally studied herein.
Four typical condensation styles, including the filming style, periodic-dropwise style, irregular-dropwise style and slow-growth-dropwise style, were concluded based on the time-series characteristics, and the condensation styles distribution was obtained.
As the visualized analysis result, differences between the pre- and post-window icon illustrate the change in the time series pattern characteristics.
Moreover, the HANTS method did not preserve the original date in the time series; temporal characteristics revealing critical phenology details were drowned (Fig. 5).
The fact that multiplying the methods and studied parameters did not increase the chance of getting significant results for both flow and tidal volume could be associated with inherent limitations of such methods applied to short and highly noisy time series, patient characteristics or possible presence of unknown covariates.
