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The mean estimates for this year: $2.57.
Parameter values are set to the mean estimates from the data.
All results reported are the mean estimates across all bootstrap samples.
Furthermore, Figure19 shows the mean estimates of the IMFs and residue by the simulation-based SEMD with 200 replications.
The ability of mixed logit to re-parameterize the mean estimates of random parameters, to establish heterogeneity associated with observable influence makes it even more attractive.
The pharmacokinetic parameters summarized in Table 7 are the mean estimates obtained from 31 subjects, who completed all periods of the study.
Table 2 shows the mean estimates derived from the linear mixed model of different parameters of iron metabolism for all patients per group at all time points.
We repeated the simulations N=1,000 times and calculated the mean estimates, the root mean square errors (RMSEs) and the mean absolute errors (MAEs).
However, there is still a significant positive relationship for the mean estimates, and the country totals are remarkably close, particularly for large countries (Figure 4c).
As the sample size n increases, the mean estimates of the parameters tend to be closer to the true parameter values.
From the results, we can verify that as the sample size n increases, the mean estimates of the parameters tend to be closer to the true parameter values, since RMSEs decay toward zero.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com