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Survival models using Kaplan-Meier (Williams, 1995) estimates were implemented using SUDAAN SUDAAN Statistical Software Centree, 2008).
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Imputation was performed using ' mi impute regress' for a normally distributed outcome and ' mi impute logit' for a binary outcome, and Rubin's rules were implemented using ' mi estimate' in Stata version 12.1 [ 11].
All regression analyses were implemented using generalized estimating equation methods [in SAS version 9.3 (SAS Institute, Cary, North Carolina, USA) and STATA version 11.2 (STATA Corp., College Station, Texas, USA)], with population-averaged models with robust standard errors accounting for the individual correlation across multiple observations over time.
Additional analyses were implemented using either Generalised Estimating Equations.
Using the HMF concentration in the control run as the inhibitor tolerance limit, an estimated solid loading of approximately 38% can be implemented using pH profiling pretreated whole slurry of FS-10 without detoxification.
Communication between nodes was implemented using MPI [34].
For continuous features, the kernel density estimation [KDE; the estimate is implemented by MATLAB's "ksdensity" function, using a normal kernel function and a window parameter (bandwidth) that is a function of the number of points in the sample] [ 49] is employed to acquire the empirical probability density function f (x|E) for essential genes and f x | E ¯ for non-essential genes [ 49].
The implementation of this estimate could be implemented via using fast N-point DFT algorithm three times.
Two commonly used error models were implemented.
The test was implemented in RAxML using the same data partitions used to estimate our phylogeny.
The mean background rate was implemented into sequenceLDhot using the previously estimated interval data.
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