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This is primarily because it tends to group together sites that evolve at similar rates of evolution, reducing the need for additional parameters to describe variation in rates across sites within a given group of sites.
The ICC is a statistic that condenses the reproducibility of a parameter for a given group of subjects.
It also forms a discriminant function (DF) for each group as in Eq. (4): f(G_{i} ) = k_{i} + mathop sum limits_{j = 1}^{n} w_{ij} p_{ij}, (4 where i is the number of groups (G), k i the constant inherent to each group, n the number of parameters used to classify a set of data into a given group, w j the weight coefficient, assigned by DA to a given selected parameter (p j ).
For a given choice of parameters, the network exhibits a number of oscillatory behaviours.
For a given vector of parameters, the predicted probability density for the target-related decision times is given by Eqs.
We observe similar average rS across most datasets for a given set of parameters.
For a given set of network parameters, statistics on the DT is accumulated over 200 simulations.
Consequently, the ranking for a given value of the parameters may be of limited value.
For a given set of simulation parameters, we create 100 replicate data sets.
For a given observed network x, parameter estimates indicate the strength of effects in the data.
Furthermore, the log odds trajectory from years one to two for a given treatment group was allowed to differ from the subsequent log odds trajectory for that treatment group through the inclusion of an additional segmented regression parameter.
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