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To estimate Ne based on multiple temporal sampling periods for the Greenland population, we used MLNE 2.3 while assuming 1) a closed population (NeCLOSED), and 2) accounting for immigration from a potential source population (NeOPEN).
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On the other hand, real-time DNA microarrays are capable of taking multiple temporal samples of a binding process [7 9].
Two general approaches to estimating Ne were explored: 1) analyzing single time period population samples, and 2) analyzing multiple temporal samples from the same population.
Multiple temporal samples within each simulation are not entirely independent, but (as shown in Results) overall replication was more than sufficient to produce robust measures of central tendency.
From the original dataset, we removed all but one set of sequences in cases where there were multiple temporal samples from a single host.
In MSE analysis (Costa et al. 2002, 2005), each single-trial time series is downsampled to multiple temporal scales and sample entropy (SE) (Richman and Moorman 2000) is calculated for each scale.
We next employ a highly efficient coalescent-based approach that takes advantage of both our temporal sampling scheme and use of multiple independently-evolving loci.
Furthermore, sub-sampling technique can also be applied in pre-processing to realize multiple sub-sources, such as the MD video coder based on spatial sampling [9] and the MD video coder based on temporal sampling [10].
The temporal sampling interval is 0.0015 s.
The temporal sampling rate is θ = 10 sample/sec.
Then adaptive temporal sampling will be applied, which is introduced in Section "Adaptive temporal sampling in pre-processing".
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