Sentence examples for impact datasets from inspiring English sources
The number of observations in volcanic impact datasets can affect data interpretation and statistical analysis.
Laboratory experiments are beneficial as they can be repeated to generate large impact datasets.
This is largely due to its extensive use in existing impact datasets and applicability to hazard model outputs at the time.
A brief discussion of combining impact datasets (hybrid data) is warranted as this is the most likely approach for deriving volcanic fragility functions given the limited availability of impact data.
As discussed in Wilson et al. (2014), the selection of a HIM must consider: (1) the HIM's appropriateness to describe a range of infrastructure impact intensities; (2) the ease of HIM measurement in the field or laboratory; (3) the applicability of the HIM to hazard model outputs; and (4) which HIM has been used in existing impact datasets.
The sensitivity analysis also considered the effect of the applied weightings and included analysis of unweighted values and of both main stage and economic impact datasets.
Different sources of epistemic (systematic) uncertainty are associated with HIMs and the volcanic impact dataset (Rossetto et al. 2014a).
Data quality rating Overall quality of the impact dataset used based on the quality rating scheme in Table 3. Number of observations The total number of observations (data points) used to derive fragility and vulnerability functions.
We also explored the impact of dataset parameters on topological accuracy.
We argue that any EC-funded project should make its full impact assessment dataset available to the scientific community shortly after the conclusion of the project.
This study clearly demonstrate the impacts of dataset selection on sensitivity of drought index computation, which has significant implications for proper usage of drought indices and related assessments, and potentially provide some valuable references for future researches on drought indices improvements.
