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The robust bootstrap is a computer-intensive inference method for robust regression estimators which is computationally simple (because we do not need to re-compute the robust estimate with each bootstrap sample) and robust to the presence of outliers in the bootstrap samples.
Open image in new window Fig. 5 Daily returns of Dow Jones Industrial Average (DJIA) index observed from October 2, 1928 to August 30, 2013 Open image in new window Fig. 6 Sample and robust first order cross-correlations computed with subsamples of size T 1000 using a rolling window of both the DJIA daily returns (top panel) and its outlier-corrected counterpart (bottom panel).
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The current IRMA implementation employs 4 registration algorithms and assesses the warped images with a battery of 11 distance metric measurements using sophisticated sampling and robust statistical estimates.
Versatile sampling and robust 1H-NMR methods have improved disease diagnosis [9] [12] and personalized healthcare [13] [15], and have provided an important tool for the characterization of genetic variations [16].
TJ conducted log-binomial and logistic analyses, with adjustment for sampling and robust variance estimators and helped edit the manuscript.
With the use of microdissected, paired breast tissue samples and robust statistical analysis, we sought to minimize potential biases elicited by small the sample size.
The true value could be higher or lower than our point estimator from which we have calculated the clinical relevance, and future studies, using larger samples and robust methodology, may clarify the true point estimate and the clinical effectiveness of OMT for LBP.
The NPI+ will enable a more sophisticated personalised treatment tool for BC patients by providing: (1) improved prognostic analysis, (2) predict risk of disease recurrence, (3) provide health economic savings through appropriate targeting of treatment, (4) NPI+ uses routine clinical samples and robust laboratory methods integrating easily into current international clinical practice.
We measure multimedia service delivery performance over standards-conforming WiMAX testbeds in Finland and Portugal, and evaluate the benefits of voice sample aggregation and robust header compression (ROHC) in practice.
Here, a start has been made to understand their behavior in relation to paint composition in a sample efficient and robust manner using DoE.
The large sample size and robust multilevel multivariable modelling of factors associated with overall satisfaction indicated the need for adjustment for these when comparing ICUs.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com