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PMSE, expressed as follows, is adopted as an evaluation index: {text{PMSE}} = frac{1}{N}sumlimits_{k = 1}^{N} {e^{2} (k)}uppi, (3)where N is the fitting sample size.
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Regarding fitting samples sizes, we can observe a rapid decrease in RMSE and MAE from 80 to 200 instances.
A 3D SGE sequence with the parameters: TR = 10 ms, TE = 3 ms, FA = 10 °, voxel size = 120 × 120 × 120 μm and NEX = 10 resulted in the best fitting for sample size, image quality, scanning time and artifacts.
The drawback of explicit state length density is that there are more parameters to estimate, which may lead to over-fitting when sample size is small.
This suggests some asymmetry of the goodness of fit testing: whereas increased sample size minimizes incorrect power law fitting of a multi-exponential process at sample sizes of n = 640 (Figures 3,6,7), power law data could still be incorrectly fitted with multi-exponential functions in a majority of trials due to the larger number of free parameters (Table 1).
I'm fitting into sample sizes.
Those that did not, were hampered by small sample size or poorly fitting curves.
Markov model depicts the state transition distribution of random variables, with advantages of low requirement to sample size and high fitting effect for short-term characteristics [12].
Sample size considerations for fitting of frequency distributions.
We also varied the total number of observations to determine the impact of sample size on model fitting; these values approximate a single night (40) or multiple nights (160, 320, 640) of stage transitions typical of standard human polysomnograms.
We ask therefore, under what conditions one distribution is likely to be mistaken for the other in terms of fitting, and consider the effects of sample size and the parameters of the distributions using simulation methods.
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