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To the best of our knowledge, this is the first study to show how increased variance of anthropometric measurements can affect outcome measures in obesity surveillance.
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In the remainder of this blog post we discuss the challenges of multi-agent RL, show how to train multi-agent policies with these existing algorithms, and also how to implement specialized algorithms that can deal with the non-stationarity and increased variance of multi-agent environments.
Increased variance also reduces success and speed.
Note the increased variance in spike threshold in the soma in comparison to the axon.
We have shown how increased adversity leads to increased subjective uncertainty, as measured by subjective variance.
In addition, there was variation between individuals in how their bone mineral density changed over time (P<0.001), shown by the increasing variance in both groups over the three years.
To examine how differences in variation might be influencing our Res scores, we plotted the distribution of Res scores for each site, sorting the sites by increasing variance (Figure 1H).
Increased temporal variance in life-history traits is generally predicted to decrease individual fitness and population growth.
Addition of health variables seldom increases variance accounted for in each domain beyond these four dimensions.
Nevertheless, our analysis provides evidence of how a network modeling approach can increase the variance explained and, moreover, provide interpretable models of genetic interaction.
This multilayered approach allows students to visualize how increasing sample size reduces variance around the mean and may increase statistical power.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com