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Sentences for "bootstrapping "
(HMMER's construction procedure slightly modifies the input alignment in ways that are usually unimportant, but which matter to bootstrapping in RIO.
Bootstrapping The use of bootstrapping with mode estimation had little or no affect on bias, except that bias increased slightly for the lognormal original distribution (Figure 4f,4g).
Increased Performance of the Bootstrapped Mode Estimators Bootstrapping clearly improved the variance of the mode estimators.
The bootstrapping probably acts to "smooth" the coarseness and irregularity that otherwise might cause inaccurate estimation of the center of location.
The same pattern was seen in the analysis of divergence times (Figure 6), where RPM and HRM mode estimates exhibited a large difference (10%) without bootstrapping and a much smaller difference (1%) with bootstrapping.
Although bootstrapping already is used to calculate the mode (M HRMB or M RPMB ), that must be considered separately.
The bootstrapping should be accomplished by taking the mean of the bootstrapped mode estimates and by using a relatively large number of replications, such as 1,000 or more [ 17 ] .
Given that we only analyzed about 300 QuartOPs using all three approaches it would be premature to generalize our findings, however, other analyses that utilized both bootstrapping and Bayesian posterior probabilities also found bootstrapping to be more conservative than posterior probabilities calculated using Bayesian methods with Markov chain Monte Carlo sampling (e.
In a recent study comparing these adjustments with other types of statistics in a different setting, Steyerberg et al [ 22 ] found that the split-sample approach tended to underestimate performance, cross-validation performed poorly on some statistics that were not normally distributed, and bootstrapping performed best overall.
A heuristic search without bootstrapping also showed the Dd myoI myosin as a branch from class VII and domain analysis shows that Dd myoI has the MyTH4 domain found in other class VII myosins.
Of the approximately 30 added centroids, most appeared to represent local minima, as they were centroids that were poorly reproduced in bootstrapping experiments (see Materials and methods) and identified few genes that had coherent patterns of expression (data not shown).
The final centroids identified by the fuzzy clustering method showed little dependence on the eigen vectors used to seed the process, as evidenced by bootstrapping analysis.
More than 50% of the final centroids were identified in 90% of the bootstrapping trials in which PCA was performed on a random sample of the data, despite the fact the most of the eigen vectors were significantly different in each trial (see Materials and methods).
Bootstrapping To estimate the dependence of the procedure on the initial dataset, a bootstrapping method was applied in which the fuzzy k-means protocol was repeated 100 times, each time on 4,373 genes chosen randomly from dataset B, with k = 102.
4 more results not shown.
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