Bootstrap Inference for Multiple Imputation
Bootstraps and imputes incomplete datasets. Then performs inference on estimates obtained from analysing the imputed datasets as proposed by von Hippel (2018) <arXiv:1210.0870v9>.

Bootstraps and imputes incomplete datasets. Then performs inference on estimates obtained from analysing the imputed datasets as proposed by von Hippel and Bartlett (2019) <arXiv:1210.0870v10>.

Bootstrapped confidence intervals for (negative) likelihood
ratio tests
This package computes appropriate confidence intervals for the
likelihood ratio tests commonly used in medicine/epidemiology.  It is
particularly useful when the sensitivity or specificy in the sample is
100%.  Note that this does not perform the test on nested models--for that,
see epicalc::lrtest.

Bootstrapped Confidence Intervals for (Negative) Likelihood
Ratio Tests
Computes appropriate confidence intervals for the likelihood ratio tests commonly used in medicine/epidemiology, using the method of Marill et al. (2015) <doi:10.1177/0962280215592907>.  It is particularly useful when the sensitivity or specificity in the sample is 100%.  Note that this does not perform the test on nested models--for that, see 'epicalc::lrtest'.

Computes appropriate confidence intervals for the likelihood ratio tests commonly used in medicine/epidemiology.  It is particularly useful when the sensitivity or specificity in the sample is 100%.  Note that this does not perform the test on nested models--for that, see 'epicalc::lrtest'.

boot, doParallel, foreach, plsRglm, pls, spls, bipartite,
mvtnorm
knitr, markdown, plsdof, prettydoc, rmarkdown
Bootstrap Hyperparameter Selection for PLS Models and Extensions
c(
person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@utt.fr", comment = c(ORCID = "0000-0002-0837-8281")),
person(given = "Jeremy", family= "Magnanensi", role = c("aut"), email = "jeremy.magnanensi@gmail.com"),
person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-4615-1512")))
Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>),
Jeremy Magnanensi [aut],
Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>)
Several implementations of non-parametric stable bootstrap-based techniques to determine the numbers of components for Partial Least Squares linear or generalized linear regression models as well as and sparse Partial Least Squares linear or generalized linear regression models. The package collects techniques that were published in a book chapter (Magnanensi et al. 2016, 'The Multiple Facets of Partial Least Squares and Related Methods', <doi:10.1007/978-3-319-40643-5_18>) and two articles (Magnanensi et al. 2017, 'Statistics and Computing', <doi:10.1007/s11222-016-9651-4>) and (Magnanensi et al. 2021, 'Frontiers in Applied Mathematics and Statistics', accepted.).