arima to automatically select and estimate an ARFIMA model.
However, together with the extracted TF-to-gene relations, the regression matrix was constructed according to equation 9. LARS was used to select and estimate the variables and calculate the Cp.
The EAC considered it would have been better to select and estimate the population consistent with the scope (i.e., people having a clinical measurement of BP), estimate the likely prevalence of AF in this population, and calculate forwards from this point, using sensitivity analyses as appropriate.
Only the important representative features are selected, and their estimated regression coefficients are updated.
We also tried different cutoffs in the selected variables and estimated the corresponding sensitivity (SENS), specificity (SPEC), positive predictive value (PPV) and negative predictive value (NPV).
The accuracies of the created individual diagnostic models for both the training and test sets are shown in Table 2, and the selected variables and estimated parameters that were created by the MLR are summarized in Additional files 15, 16, 17, 18, 19, 20, 21 and 22.
For most traits, the predictive ability of the marker-based EBV was not substantially lower for traits measured at a late age, although late traits were only recorded on selected individuals and estimated heritabilities for late traits were generally lower than for the corresponding traits measured at a younger age.
We then used the selected distribution and estimates of regional prevalence to calculate and map statistical power to detect hotspots and coldspots, and estimate the p-value from Monte Carlo significance tests that specific lease blocks are in fact hotspots or coldspots relative to regional average abundance.
Evidence for recombination within each gene family alignment were tested for with the Pairwise Homoplasy Index (PHI) [44] and GARD [40] using nucleotide substitution models selected above and estimating substitution frequencies and a proportion of invariable sites from the data with 4 rate categories in a gamma distribution.
Quartet Decomposition was performed on 100 topologies per gene family inferred by maximum likelihood from 100 bootstrap samples of each alignment using phyML [66] using the nucleotide substitution models selected above and estimating substitution frequencies and a proportion of invariable sites from the data with 4 rate categories in a gamma distribution where required by the model.
