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These last two approaches were implemented either using the model in expression (2a) or the interaction model expression (3a).
The models can be implemented either mathematically or computationally, and can model either stepwise (discrete) or continuous evolutionary change.
Each model was implemented either with or without phylogenetic adjustment.
We note that a limitation of the Riska et al [ 42] approach is that using the same mean squares for the estimation of different causal components generates covariance between the estimates which is not accounted for in the model as implemented either by Riska et al [ 42, 55] or here (i.e. the off-diagonal elements of the V matrix are set to zero, see below).
To develop prediction models, we utilized likelihood cross-validated penalized logistic regression models which implemented either an L1 penalty (Lasso) [22] or an L2 penalty (Ridge) using the R package 'penalized' [23].
We implement our model efficiently as the software package COMPETE.
Crawford would like to see New Zealand implement a model of regulation and taxation similar to Colorado.
In March, Indiana medical practitioners began collaborating with Montaner to implement his model.
We used the NetLogo environment [21] to implement the model.
RAM wrote the computer programs to implement the model.
Instead we implement the model with a Bayesian approach.
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