Sentence examples for data series and methods from inspiring English sources
We would like to express our gratitude towards them and towards scientists and institutions that have made their data series and methods available for this study.
On the other hand, based on observed data, time-dependent approaches and time series methods have their own advantages: focusing on the inter-relation and consistency of existing data series, and taking time as its only independent variable without consideration of other factors temporarily.
The quality and reliability of assessments based on the Sustainability Indicator System (SIS) such as the one we presented in this paper depends on the appropriateness of the selected indicators, the availability of valid data series, targets determined and the evaluation method applied, e.g. based on the distance-to-target approach.
A Bayesian approach may offer advantages in accounting for uncertainty in estimated parameters, as has been recently demonstrated in an application of empirical Bayes methods for the surveillance of multiple data series using statistical process control methods [ 8].
We employ surrogate data testing and methods of nonlinear time series analysis.
However, being quite intuitive and direct, it has become one of the most used adaptive methods to deal with data series originating from nonlinear and non-stationary processes.
To test the method we had a data series of 20 years, and we could have extended the window to about ten years.
Data and methods: We used time series of meningitis incidence from 1986 through 2006 for 38 districts in Niger.
Using the uniquely detailed hydrochemical datasets generated under the Demonstration Test Catchments programme in England, the efficacy and robustness of change detection methods for hydrochemical data series is assessed.
The significance of Fisher's and Pearson's tests was adjusted for multiple testing according to Bonferroni method within corresponding data series.
Principal component analysis (PCA) is a method that transforms multiple data series into uncorrelated data series.
