What is an efficient workflow for large-datasets with dense sampling coverage and thus high-quality COI barcoding output, may be inapplicable for datasets in little known and putatively under-sampled taxa.
In comparison with worst-case regression, it reduces the estimation variability and is able to produce reasonable estimation results even when regression on incomplete datasets is inapplicable.
A strict molecular clock has been rejected in analyses of most empirical datasets, and is inapplicable to data in which rate shifts occur, so relaxed molecular clock models are used widely (reviewed in [ 10]).
It must be also noted that the FASS, MB and S-methods turned out to be inapplicable to many instances from out benchmark dataset, due to restrictions imposed onto the alignment length and the number of sequences, while demonstrating good performance in the remaining cases.
The other issue was the lack of lifestyle factors for smoking, drinking, diet, obesity and physical activities in our dataset, which made further confounding control inapplicable.
Although applicable in cases of large datasets with few missing values, this is far from ideal and inapplicable in our case, as it is indeed the objective of the challenge to predict the masked data.
However, the two orders of magnitude difference in dataset size (462 genes versus 10 proteins) made the standard correlation methods inapplicable.
Yet, missing observations scattered over the dataset restrict the number of effectively available datapoints and make classical regression techniques inaccurate or inapplicable.
501 and inapplicable in diversity cases.
It is not, however, entirely inapplicable even there.
The entire set of legal categories would be inapplicable.
