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The average local error decreases respectively 3.86%.
The daily average local error is 0.06% for 80% summarization, whereas, it becomes 0.14% for 90% summarization.
The global error is on average 76.81%, 47.57% and 58.12% lower than the average local error for the accelerometer, battery and noise.
Given that the two metrics are relative, the global error can be compared to the average local error among the citizens.
The average local error under 100% of participating citizens for daily and weekly summarization is 0.03 whereas the global error is 0.01 respectively.
Results confirm the trend of Figure 15, however, the average local error and global error for daily summarization and 100% of the participating citizens are 94.55% and 87.41% higher than these of the empirical summarization.
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The global error for daily summarization is 83.44% lower on average than the average local errors.
Based on both average and local error measurements, it is shown that void growth is underestimated with multiscale schemes, while predictions are significantly improved with the DVC-FE approach.
Therefore, we observe that the average local ancestry prediction error is increased as distance between ancestral locations is increased.
The striking difference between the average local and global errors occurs because of the cancellations in the local errors occurring in aggregation.
Fig. 2 Relationship between average localization errors and ranging errors.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com