R-universe search: topic:bootstrap

rstudio

bslib:Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'

Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports 'Bootstrap' 3, 4 and 5 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.

Maintained by Carson Sievert. Last updated 26 days ago.

bootstrap htmltools rmarkdown sass shiny

511 stars 18.02 score 5.1k scripts 4.3k dependents

easystats

parameters:Processing of Model Parameters

Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).

Maintained by Daniel Lüdecke. Last updated 10 days ago.

beta bootstrap ci confidence-intervals data-reduction easystats fa feature-extraction feature-reduction hacktoberfest parameters pca pvalues regression-models robust-statistics standardize standardized-estimates statistical-models

454 stars 15.67 score 1.8k scripts 56 dependents

dreamrs

fresh:Create Custom 'Bootstrap' Themes to Use in 'Shiny'

Customize 'Bootstrap' and 'Bootswatch' themes, like colors, fonts, grid layout, to use in 'Shiny' applications, 'rmarkdown' documents and 'flexdashboard'.

Maintained by Victor Perrier. Last updated 9 months ago.

bootstrap shiny shiny-applications shiny-themes

228 stars 12.03 score 546 scripts 47 dependents

mayer79

confintr:Confidence Intervals

Calculates classic and/or bootstrap confidence intervals for many parameters such as the population mean, variance, interquartile range (IQR), median absolute deviation (MAD), skewness, kurtosis, Cramer's V, odds ratio, R-squared, quantiles (incl. median), proportions, different types of correlation measures, difference in means, quantiles and medians. Many of the classic confidence intervals are described in Smithson, M. (2003, ISBN: 978-0761924999). Bootstrap confidence intervals are calculated with the R package 'boot'. Both one- and two-sided intervals are supported.

Maintained by Michael Mayer. Last updated 8 months ago.

bootstrap confidence-intervals statistical-inference statistics

16 stars 8.62 score 104 scripts 17 dependents

bioc

nullranges:Generation of null ranges via bootstrapping or covariate matching

Modular package for generation of sets of ranges representing the null hypothesis. These can take the form of bootstrap samples of ranges (using the block bootstrap framework of Bickel et al 2010), or sets of control ranges that are matched across one or more covariates. nullranges is designed to be inter-operable with other packages for analysis of genomic overlap enrichment, including the plyranges Bioconductor package.

Maintained by Michael Love. Last updated 5 months ago.

visualization genesetenrichment functionalgenomics epigenetics generegulation genetarget genomeannotation annotation genomewideassociation histonemodification chipseq atacseq dnaseseq rnaseq hiddenmarkovmodel bioconductor bootstrap genomics matching statistics

27 stars 8.16 score 50 scripts 1 dependents

mthulin

boot.pval:Bootstrap p-Values

Computation of bootstrap p-values through inversion of confidence intervals, including convenience functions for regression models and tests of location.

Maintained by Måns Thulin. Last updated 25 days ago.

bootstrap p-value regression-models

4 stars 7.89 score 36 scripts 3 dependents

spsanderson

TidyDensity:Functions for Tidy Analysis and Generation of Random Data

To make it easy to generate random numbers based upon the underlying stats distribution functions. All data is returned in a tidy and structured format making working with the data simple and straight forward. Given that the data is returned in a tidy 'tibble' it lends itself to working with the rest of the 'tidyverse'.

Maintained by Steven Sanderson. Last updated 5 months ago.

bootstrap density distributions ggplot2 probability r-language simulation statistics tibble tidy

34 stars 7.73 score 66 scripts 1 dependents

jasdumas

shinyLP:Bootstrap Landing Home Pages for Shiny Applications

Provides functions that wrap HTML Bootstrap components code to enable the design and layout of informative landing home pages for Shiny applications. This can lead to a better user experience for the users and writing less HTML for the developer.

Maintained by Jasmine Daly. Last updated 28 days ago.

bootstrap r-shiny shiny ui-design

115 stars 7.29 score 85 scripts 2 dependents

statistikat

surveysd:Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel Designs

Calculate point estimates and their standard errors in complex household surveys using bootstrap replicates. Bootstrapping considers survey design with a rotating panel. A comprehensive description of the methodology can be found under <https://statistikat.github.io/surveysd/articles/methodology.html>.

Maintained by Johannes Gussenbauer. Last updated 13 days ago.

bootstrap error-estimation survey cpp

9 stars 7.04 score 67 scripts

business-science

modeltime.resample:Resampling Tools for Time Series Forecasting

A 'modeltime' extension that implements forecast resampling tools that assess time-based model performance and stability for a single time series, panel data, and cross-sectional time series analysis.

Maintained by Matt Dancho. Last updated 1 years ago.

accuracy-metrics backtesting bootstrap bootstrapping cross-validation forecasting modeltime modeltime-resample resampling statistics tidymodels time-series

19 stars 6.64 score 38 scripts 1 dependents

tzerk

RLumShiny:'Shiny' Applications for the R Package 'Luminescence'

A collection of 'shiny' applications for the R package 'Luminescence'. These mainly, but not exclusively, include applications for plotting chronometric data from e.g. luminescence or radiocarbon dating. It further provides access to bootstraps tooltip and popover functionality and contains the 'jscolor.js' library with a custom 'shiny' output binding.

Maintained by Christoph Burow. Last updated 6 days ago.

bootstrap jscolor luminescence luminescence-dating shiny shiny-applications tooltip

7 stars 6.23 score 67 scripts 2 dependents

smeekes

bootUR:Bootstrap Unit Root Tests

Set of functions to perform various bootstrap unit root tests for both individual time series (including augmented Dickey-Fuller test and union tests), multiple time series and panel data; see Smeekes and Wilms (2023) <doi:10.18637/jss.v106.i12>, Palm, Smeekes and Urbain (2008) <doi:10.1111/j.1467-9892.2007.00565.x>, Palm, Smeekes and Urbain (2011) <doi:10.1016/j.jeconom.2010.11.010>, Moon and Perron (2012) <doi:10.1016/j.jeconom.2012.01.008>, Smeekes and Taylor (2012) <doi:10.1017/S0266466611000387> and Smeekes (2015) <doi:10.1111/jtsa.12110> for key references.

Maintained by Stephan Smeekes. Last updated 2 months ago.

bootstrap dickey-fuller hypothesis-test time-series unit-root openblas cpp

10 stars 5.91 score 27 scripts

doi-usgs

EGRETci:Exploration and Graphics for RivEr Trends Confidence Intervals

Collection of functions to evaluate uncertainty of results from water quality analysis using the Weighted Regressions on Time Discharge and Season (WRTDS) method. This package is an add-on to the EGRET package that performs the WRTDS analysis. The WRTDS modeling method was initially introduced and discussed in Hirsch et al. (2010) <doi:10.1111/j.1752-1688.2010.00482.x>, and expanded in Hirsch and De Cicco (2015) <doi:10.3133/tm4A10>. The paper describing the uncertainty and confidence interval calculations is Hirsch et al. (2015) <doi:10.1016/j.envsoft.2015.07.017>.

Maintained by Laura DeCicco. Last updated 2 years ago.

bootstrap egret usgs water-quality-trends

9 stars 5.46 score 32 scripts

alec-stashevsky

blocklength:Select an Optimal Block-Length to Bootstrap Dependent Data (Block Bootstrap)

A set of functions to select the optimal block-length for a dependent bootstrap (block-bootstrap). Includes the Hall, Horowitz, and Jing (1995) <doi:10.1093/biomet/82.3.561> subsampling-based cross-validation method, the Politis and White (2004) <doi:10.1081/ETC-120028836> Spectral Density Plug-in method, including the Patton, Politis, and White (2009) <doi:10.1080/07474930802459016> correction, and the Lahiri, Furukawa, and Lee (2007) <doi:10.1016/j.stamet.2006.08.002> nonparametric plug-in method, with a corresponding set of S3 plot methods.

Maintained by Alec Stashevsky. Last updated 23 days ago.

block-bootstrap block-resampling blocklength boot bootstrap depedent-bootstrap dependent horowitz inference meboot politis resample stats time time-series time-series-analysis tseries

4 stars 4.78 score 8 scripts

roga11

MSTest:Hypothesis Testing for Markov Switching Models

Implementation of hypothesis testing procedures described in Hansen (1992) <doi:10.1002/jae.3950070506>, Carrasco, Hu, & Ploberger (2014) <doi:10.3982/ECTA8609>, Dufour & Luger (2017) <doi:10.1080/07474938.2017.1307548>, and Rodriguez Rondon & Dufour (2024) <https://grodriguezrondon.com/files/RodriguezRondon_Dufour_2024_MonteCarlo_LikelihoodRatioTest_MarkovSwitchingModels_20241015.pdf> that can be used to identify the number of regimes in Markov switching models.

Maintained by Gabriel Rodriguez Rondon. Last updated 1 months ago.

autoregressive bootstrap hypothesis-testing likelihood-ratio-test markov-chain moments monte-carlo non-linear regime-switching time-series openblas cpp openmp

5 stars 4.18 score 3 scripts

jeksterslab

bootStateSpace:Bootstrap for State Space Models

Provides a streamlined and user-friendly framework for bootstrapping in state space models, particularly when the number of subjects/units (n) exceeds one, a scenario commonly encountered in social and behavioral sciences. For an introduction to state space models in social and behavioral sciences, refer to Chow, Ho, Hamaker, and Dolan (2010) <doi:10.1080/10705511003661553>.

Maintained by Ivan Jacob Agaloos Pesigan. Last updated 2 months ago.

bootstrap state-space-model

4.01 score 51 scripts

mightymetrika

bootwar:Nonparametric Bootstrap Test with Pooled Resampling Card Game

The card game War is simple in its rules but can be lengthy. In another domain, the nonparametric bootstrap test with pooled resampling (nbpr) methods, as outlined in Dwivedi, Mallawaarachchi, and Alvarado (2017) <doi:10.1002/sim.7263>, is optimal for comparing paired or unpaired means in non-normal data, especially for small sample size studies. However, many researchers are unfamiliar with these methods. The 'bootwar' package bridges this gap by enabling users to grasp the concepts of nbpr via Boot War, a variation of the card game War designed for small samples. The package provides functions like score_keeper() and play_round() to streamline gameplay and scoring. Once a predetermined number of rounds concludes, users can employ the analyze_game() function to derive game results. This function leverages the 'npboottprm' package's nonparboot() to report nbpr results and, for comparative analysis, also reports results from the 'stats' package's t.test() function. Additionally, 'bootwar' features an interactive 'shiny' web application, bootwar(). This offers a user-centric interface to experience Boot War, enhancing understanding of nbpr methods across various distributions, sample sizes, number of bootstrap resamples, and confidence intervals.

Maintained by Mackson Ncube. Last updated 1 years ago.

bootstrap data-science resampling statistics

4.00 score 6 scripts

dmolitor

bolasso:Model Consistent Lasso Estimation Through the Bootstrap

Implements the bolasso algorithm for consistent variable selection and estimation accuracy. Includes support for many parallel backends via the future package. For details see: Bach (2008), 'Bolasso: model consistent Lasso estimation through the bootstrap', <doi:10.48550/arXiv.0804.1302>.

Maintained by Daniel Molitor. Last updated 3 months ago.

bolasso bootstrap lasso variable-selection

4 stars 3.90 score 7 scripts

twolodzko

kernelboot:Smoothed Bootstrap and Random Generation from Kernel Densities

Smoothed bootstrap and functions for random generation from univariate and multivariate kernel densities. It does not estimate kernel densities.

Maintained by Tymoteusz Wolodzko. Last updated 2 years ago.

bootstrap density kernel-density random-generation simulation cpp

3 stars 3.35 score 15 scripts

gregorkb

QregBB:Block Bootstrap Methods for Quantile Regression in Time Series

Implements moving-blocks bootstrap and extended tapered-blocks bootstrap, as well as smooth versions of each, for quantile regression in time series. This package accompanies the paper: Gregory, K. B., Lahiri, S. N., & Nordman, D. J. (2018). A smooth block bootstrap for quantile regression with time series. The Annals of Statistics, 46(3), 1138-1166.

Maintained by Karl Gregory. Last updated 3 years ago.

bootstrap quantile-regression time-series

2 stars 3.00 score 1 scripts

noramvillanueva

seq2R:Simple Method to Detect Compositional Changes in Genomic Sequences

This software is useful for loading '.fasta' or '.gbk' files, and for retrieving sequences from 'GenBank' dataset <https://www.ncbi.nlm.nih.gov/genbank/>. This package allows to detect differences or asymmetries based on nucleotide composition by using local linear kernel smoothers. Also, it is possible to draw inference about critical points (i. e. maximum or minimum points) related with the derivative curves. Additionally, bootstrap methods have been used for estimating confidence intervals and speed computational techniques (binning techniques) have been implemented in 'seq2R'.

Maintained by Nora M. Villanueva. Last updated 4 months ago.

bootstrap change-points dna-sequences genome-analysis machine-learning nonparametric-statistics regression fortran

3.00 score 10 scripts

nomahi

dmetatools:Computational tools for meta-analysis of diagnostic accuracy test

Computational tools for meta-analysis of diagnostic accuracy test. This package enables computations of confidence interval for the AUC of summary ROC curve and some related AUC-based inference methods.

Maintained by Hisashi Noma. Last updated 3 years ago.

auc bootstrap diagnostic-tests meta-analysis summary-roc-curve

2.70 score 2 scripts

mightymetrika

exactamente:Explore the Exact Bootstrap Method

Researchers often use the bootstrap to understand a sample drawn from a population with unknown distribution. The exact bootstrap method is a practical tool for exploring the distribution of small sample size data. For a sample of size n, the exact bootstrap method generates the entire space of n to the power of n resamples and calculates all realizations of the selected statistic. The 'exactamente' package includes functions for implementing two bootstrap methods, the exact bootstrap and the regular bootstrap. The exact_bootstrap() function applies the exact bootstrap method following methodologies outlined in Kisielinska (2013) <doi:10.1007/s00180-012-0350-0>. The regular_bootstrap() function offers a more traditional bootstrap approach, where users can determine the number of resamples. The e_vs_r() function allows users to directly compare results from these bootstrap methods. To augment user experience, 'exactamente' includes the function exactamente_app() which launches an interactive 'shiny' web application. This application facilitates exploration and comparison of the bootstrap methods, providing options for modifying various parameters and visualizing results.

Maintained by Mackson Ncube. Last updated 2 years ago.

bootstrap probability resample statistics

2.70 score 2 scripts

nt-williams

simul:Fast Simultaneous Confidence Bands Based on the Efficient Influence Function and Multiplier Bootstrap

Compute critical values for constructing uniform (simultaneous) confidence bands. The critical value is calculated using a multiplier bootstrap of the empirical efficient influence function as described by Kennedy (2019) <doi:10.1080/01621459.2017.1422737>. The multiplier bootstrap does not require resampling of the data but only simulation of the multipliers and is thus computationally efficient.

Maintained by Nicholas Williams. Last updated 4 years ago.

bootstrap confidence-intervals non-parametric-statistics cpp

5 stars 2.40 score 3 scripts

maikol-solis

sobolnp:Nonparametric Sobol Estimator with Bootstrap Bandwidth

Algorithm to estimate the Sobol indices using a non-parametric fit of the regression curve. The bandwidth is estimated using bootstrap to reduce the finite-sample bias. The package is based on the paper Solís, M. (2018) <arXiv:1803.03333>.

Maintained by Maikol Solís. Last updated 2 years ago.

bandwidth bootstrap cross-validation nonparametric-regression sensitivity-analysis

2.00 score 1 scripts