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bootstrap estimation
Posterior distributions for the three databases are presented and discussed and the consequences of implementing bootstrap estimation procedures are also shown.
      
The bootstrap estimation for variance and its robustness in linear regression is considered.
      
Bootstrap estimation of the asymptotic variances of statistical functionals
      
On bootstrap estimation of the distribution of the studentized mean
      
We consider the estimation of error rate of the linear combination classification procedure by using the leave-one-out estimation and bootstrap estimation.
      
Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences: II.
      
The statistical properties of sample estimation and bootstrap estimation of phylogenetic variability from a sample of nucleotide sequences were studied by considering model trees of three taxa with an outgroup.
      
The results of simulation showed that bootstrap estimation of the confidence level for an inferred phylogeny can be used even under unequal rates of evolution if the rate differences are not large so that the MP method is not misleading.
      
If the rate differences are large so that the MP method becomes consistently misleading, then bootstrap estimation will reinforce an erroneous conclusion on topology.
      
Statistical techniques based on bootstrap estimation are presented that are designed to aid in choosing an equating method/degree of smoothing.
      
We used bootstrap estimation to derive 95% confidence intervals for differences in the responsiveness indices.
      
Ideal bootstrap estimation of expected prediction error for k-nearest neighbor classifiers: Applications for classification and
      
Bootstrap estimation of actual significance levels for tests based on estimated nuisance parameters
      
A Semi-Parametric Quantile Function Estimator for Use in Bootstrap Estimation Procedures
      
Efficacy of joint person subset bootstrap estimation of confidence interval 55 V.
      
Only for computational simplification, the second-order parameter q was set equal to one in simulating the bootstrap estimation approach.
      
Since the results are based on non-random sampling, they are validated using a bootstrap estimation method.
      
Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences.
      
The error bars meausure variances over multiple repetitions of the bootstrap estimation experiment.
      
We constructed 95% CIs using bootstrap estimation as previ Table 1.
      
 

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