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Exact(31)
At low levels of noise, lower that 20%, non-linear methods performed well achieving performance higher than 0.7 MCC units for most of the tested datasets.
The precision, efficiency, false positive rate, limit of detection (LOD95%) and probability of detection (POD) were determined, and the results demonstrated that both bovine and ovine detection methods performed well.
Simple NDVI-based methods performed well for estimating fc regionally but overestimated fc in sparsely vegetated areas with bright soils, and areas with abundant non-photosynthetic vegetation (e.g. dry shrubs).
Despite these differences, both the Baker and Gray methods performed well in the second CAPRI assessment, placing fifth and seventh respectively out of 30 predictor groups.
All methods performed well with no errors.
Both methods performed well on our data.
Similar(29)
As expected, all methods perform well when the SNR is high, but exhibit marked differences in performance for finite SNR.
Monte Carlo simulations for three different models show that the methods perform well in finite samples.
Monte Carlo simulations for four different models show that the methods perform well in finite samples.
Monte Carlo simulations for five different models show that the methods perform well in finite samples.
It is found that both asymptotic methods perform well for small sample sizes despite being approximate procedures.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com