Exemplos de uso de Bootstrap method em Inglês e suas traduções para o Português
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Instead, a method handle(called a bootstrap method) is invoked.
The bootstrap method is performed using the processing power of current computers.
Dynamic constants are created by implementing a bootstrap method that returns the constant's value as its result.
This bootstrap method is then referenced at the location where the constant value should be used.
InvokeDynamic is actually fairly similar where the difference is that it uses a bootstrap method to bind a call site and not a constant value.
The bootstrap method is the way in which user code chooses which method needs to be called.
From the classical point of view, the maximum likelihood estimator for rho was shown to be biased anda correction based on the well-known nonparametric bootstrap method for correction was proposed and investigated.
This bootstrap method returns a CallSite object, which contains another method handle, which is the actual target of the invokedynamic call.
After validation by the bootstrap method, only seven associations could be considered stable, two of which included the outcome variable Figure 2.
The Bootstrap method verified the significance of the difference between the thyroid nodules volume measurements at US provided by the observers for a 5% alpha.
The present work was developed aiming to apply the bootstrap method in statistical radioecological data analysis and to assist the researcher in obtaining the most appropriate estimators for the population parameters.
The bootstrap methods are intensive computational methods that use resampling to calculate measures of uncertainty of the estimators, such as standard errors, bias and confidence intervals.
Using the bootstrap method, it was verified which relations between self- and hetero-perception were statistically significant at 5% of one-tailed significance Table 4.
The bootstrap method can be used to obtain an approximation of the true distribution of statistics of interest and thus assess its variability, and also allows the construction of confidence intervals and hypothesis testing.
The bootstrap methods are studied: the standard bootstrap confidence interval, the bootstrap-t confidence interval, the bootstrap percentile confidence interval, the bootstrap bcbp confidence interval and the bootstrap bca confidence interval.
The measurements were performed using the bootstrapping method.
The bootstrapping method was used to assess measurement models.
The ED90 of sugammadex calculated by isotonic regression was 2.39mg/kg, with a 95% confidenceinterval of 2.27-2.46 mg/kg, calculated by the bootstrapping method with 9,999 replicates of the sample.
The confidence intervals of the risks associated with hospitals were estimated by the method Bootstrap.
As mentioned, two were considered stable by the validation method used bootstrap.
To determine this interval,we used the bootstrap resampling method, because the population of individuals with AAT deficiency was small.
We used the bootstrap resampling method in order to determine a cut-off point and a confidence interval of 97% for dried blood spots.
Descriptive analysis of data was performed, resulting in frequency tables for qualitative variables ordinal or nominal, and the inclusion of the confidence interval for the proportion CI 95%,calculated from 1000 replicas by means of the bootstrap resampling method.
To determine the sensitivity and specificity of the eluate method, Zillmer et al. used the bootstrap resampling method, comparing the AAT values measured in serum with those measured in eluates from DBS samples in order to determine a cut-off point for AAT values in eluates; the value obtained was 2.02 mg/dL 97% CI: 1.45-2.64.
To determine the sensitivity and specificity of the eluate method, we used the bootstrap resampling method, comparing the AAT values measured in serum gold standard with those measured in eluates from dried blood spots, so as to determine a cut-off point for AAT values in eluates; the value obtained was 2.02 mg/dL 97% CI: 1.45-2.64.
The Cronbach's Alpha was calculated for each hospital n=20 and with all the sample n=40, yet still, for a better exploitation of the information,there were reliability intervals for these indices calculated through the method bootstrap and all were of a 95% reliability.
Data analysis of qualitative variables was descriptive, with frequency tables ordinal or nominal; 95% confidence intervals 96% CIs were included for proportions,calculated by a bootstrap resampling method that obtained its sample through sampling with reposition of the original sample 1,000 times.
However, our choice was different as we decided to make a robust analysis suggested by Hadi andimplemented in SYSTAT 13 in which a resampling method bootstrap with 500 samples equal to the size of samples for each cohort was added in order to obtain standard errors to helps us in the construction of confidence intervals for all r values, providing a more precise view of tracking coefficients see Table 2.
Bootstrap resampling methods have been used in some studies to improve the performance of mcp.