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That is, if we derive a posterior probability distribution function for a parameter using one dataset, we can apply that as the prior when a new dataset comes along, and thereby improve our estimates of the parameter and shrink the error bars.
More data will shrink the error bars and yield a clearer picture.
Similar(58)
The empirical Bayes approach, in the function eBays, was used to moderate the standard errors of the estimated log-fold changes and shrink the standard errors to a common value.
aNumber of microarray elements determined to be significant on the array using the empirical Bayes method to shrink the gene-wise error estimate in cadmium treated vs. control Daphnia pulex (P < 0.05).
This is used to estimate the moderated t-statistics/F-statistics for each gene, shrinking the standard error towards a common value.
In the third step an empirical Bayes approach was used to shrink the gene-wise standard errors towards a common value and a moderated t-statistic was calculated [ 66, 71].
As the semiconductor geometry shrinks, the error performance of NAND Flash memory becomes worse, thus it is greatly needed to increase the reliability by using memory signal processing and forward-error correction (FEC) methods.
So shrink the numbers?
But they shrink the sidewalk.
Shrink the payroll.
Pre shrink the linen.
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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