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These numerical methods include the application of Direct Cyclic Analysis (DCA), utilised in an automated search procedure for load-interaction plot generation and the recently developed Hybrid procedure.
Forest plot generation and statistical analyses were performed using RevMan version 5.2.
All data were imported into FCS Express DeNovo™ Softwaree, Los Angeles, CA) for plot generation and statistical analyses.
Matlab (Mathworks, Natick, MA) was used for ribbon plot generation, and low pass Butterworth filtering (1 hr).
Finally, users can download our scripts, which require R and Python, and associated databases in SQLite format to enable plot generation on their local unix machine.
A description of area plot generation is also provided in the Methods section and is illustrated in Figure 5B (and figure legend) to assist the reader.
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Collection of abstract content data was performed by manual curation and data were entered into an excel spreadsheet (Microsoft™ Excel® 2007) for statistical processing and plots generation.
Number of discarded generations was determined for each run based on visual analysis of the plot showing generation versus the log probability of observing the data.
Number of discarded generations was determined for every run based on visual analysis of the plot showing generation versus the log probability of observing the data.
We examined the output plot of generation versus log likelihood to find that stationarity was reached.
At the end of run there were not any trends in a plot of generation versus the log probability of the observed data (the log likelihood values).
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CEO of Professional Science Editing for Scientists @ prosciediting.com