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(b) We refited the smoothing spline model using and the observed woman-years, to create a resampled hazard rate function, (t), generated under the model.
3. We repeated 1,000 times: (a) We took a random sample with replacement of the residuals,, t = 1,..., T, and used these values to create a random sample of count data generated under the model using the expression.
Pseudo-observed data sets were generated under the model of adaptation described earlier, with a specific value of the mutation rate U and a specific Gamma distribution (with parameters α and β) with mean E(S).
Data were generated under the model in Equation 3, and analysed using either the reduced model in Equation 10 or the traditional model in Equation 15, using the ASReml software (Gilmour et al., 2006).
The pseudo-observed data used to infer the performance of the method are generated under the model of adaptation explained before, but the method now analyses the distributions, along time intervals (ti), of both marker frequency (f ti)) and fitness (w ti)), where ti = i × 50 generations (i = 0 6) are measured for 100 replicate populations evolving under a given U, α, and β.
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The underestimation of ρ F is even present to a larger extent when ρ F is estimated from data generated under the ordered model compared to the estimation under the true model.
The data were generated under the SEM model as the objective was to evaluate the performance of the mixed model when the SEM is expected to be preferable.
In the simulation, this correlation matrix was calculated from the data generated under the neutral model.
In this section, we present the results for the percentage of node matches and assortativity index incurred with the maximal node matching and maximal assortative matching for random networks generated under the Erdos Renyi model wherein the node weights are random numbers generated from 0 to 1.
The phylogenetic tree was generated under the substitution model HKY85 using estimated γ distribution on sites.
Trees generated under the ERM model have a index of 0, whereas PDA trees are characterized by.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com