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RStudio bootstrap functions (boot) package
Bootstrap Functions (Boot) Package, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/bootstrap+function/boot+package/pm38923619-143-19-32
Average 90 stars, based on 1 article reviews
bootstrap functions (boot) package - by Bioz Stars, 2026-09
90/100 stars

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Related Articles

other:

Article Title: Transcendent thinking counteracts longitudinal effects of mid-adolescent exposure to community violence in the anterior cingulate cortex.
Article Snippet: To confirm the robustness of findings, percentile bootstrapped confidence intervals for the effects of interest were calculated using the Bootstrap Functions (“boot”) package (Version 1.3- 28.1; Canty & Ripley, 2022) implemented in RStudio (Version 2023.06.0+421, Posit Software, PBC, Version 4.3.1) with 10,000 bootstrapped samples.

Article Title: Validation of proximity loggers to record proximity events among beef bulls
Article Snippet: The 95% CI of these metrics were obtained by bootstrapping with 1000 simulation iterations, generating data-based confidence intervals ( ) using the ‘ boot ’ package in RStudio (Version 4.3.2, RStudio, Inc.).

Article Title: Transcendent thinking counteracts longitudinal effects of mid‐adolescent exposure to community violence in the anterior cingulate cortex
Article Snippet: To confirm the robustness of findings, percentile bootstrapped confidence intervals for the effects of interest were calculated using the Bootstrap Functions (“boot”) package (Version 1.3‐28.1; Canty & Ripley, ) implemented in RStudio (Version 2023.06.0+421, Posit Software, PBC, Version 4.3.1) with 10,000 bootstrapped samples.

Article Title: A mixed-methods study on impact of active case finding on pulmonary tuberculosis treatment outcomes in India
Article Snippet: Bootstrap analysis was performed using the boot() function from the {boot} package in RStudio to estimate the uncertainty of predictor coefficients.

Gene Expression:

Article Title: Multiple faces of stress in the zebrafish ( Danio rerio ) brain
Article Snippet: .. For this, the gene expression values as log 2 of the normalized expression were used to generate bootstrapped data sets, with n = 100 data points separately for each treatment group and gender, for each gene using the R package boot ( ) and resampled ( ) in RStudio, and subsequently, random forest models were performed in a Jupyter Notebook based on Python 3. ..

Expressing:

Article Title: Multiple faces of stress in the zebrafish ( Danio rerio ) brain
Article Snippet: .. For this, the gene expression values as log 2 of the normalized expression were used to generate bootstrapped data sets, with n = 100 data points separately for each treatment group and gender, for each gene using the R package boot ( ) and resampled ( ) in RStudio, and subsequently, random forest models were performed in a Jupyter Notebook based on Python 3. ..



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