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From understanding the cell shapes, outlier fingerprint data are eliminated by the iterative data cleansing method.
Outliers in the original ultrasonic wave time (t) data are eliminated before the data analysis using Grubbs' test.
At the same time, redundant or irrelevant data are eliminated and the amount of input data is reduced.
Data are eliminated, while engine is off or GPS data are invalid (e.g., driving in tunnel, on mountain road, or underneath the viaduct).
The main reason for this is that completed data are eliminated from the address space, threads are kept busy, and memory bandwidth is not wasted on checking completed data.
Multivariate Cox regression requires complete data on all included cases so that any cases with without complete data are eliminated from the analysis.
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All positions containing gaps and missing data were eliminated.
All positions containing gaps and missing data were eliminated from the dataset (complete deletion option).
Known jumps were corrected for and some poor quality data were eliminated manually.
Furthermore each data set was evaluated using the Q-test to test for outliers with some data being eliminated.
Known jumps, identified by the operators of the observatories, were corrected for and some poor-quality data were eliminated manually.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com