# fwildclusterboot 0.3.5 2021-06-20

• Bug fix: For Rademacher and Mammen weights and cases where (2^ number of clusters) < # boostrap iterations, (deterministic ) full enumeration should have been employed for sampling the bootstrap weights. Full enumeration means the following: for e.g. 6 numbers of clusters, only 2^6 = 64 unique draws from either the Rademacher or Mammen distributions exists. Therefore, boottest() overwrites the user-provided number of bootstrap iterations to B = (2^ number of clusters) if a larger number is chosen. The bug now occured because the bootstrap weights were drawn randomly with replacement instead of using full enumeration. Note: full enumeration was introduced with version 0.3.3. Thanks to fschoner for finding the bug! see github issue #11

• Bug fix: A small bug has been fixed related to missing values in the cluster variables.

• By default, boottest() now sets an internal seed if no seed is provided by the user via the seed function argument.

• Several improvements to the documentation.

# fwildclusterboot 0.3.4 2021-05-01

• Fix CRAN errors caused by a small bug in the vignette

# fwildclusterboot 0.3.3 2021-04-12

• implements full enumeration for Rademacher and Mammen Weights if 2k < B, where k is the number of clusters and B the number of bootstrap iterations

# fwildclusterboot 0.3.2 2021-02-26

• Fixes a CRAN test error message for Oracle Solaris.

# fwildclusterboot 0.3.1 2021-02-16

• A glance.boottest() method was added, which enables the use of the modelsummary package with fwildclusterboot.
• The tidy.boottest() method is no longer exported. You can still access it via fwildclusterboot:::tidy.boottest() or by loading the generics package via library(generics).

# fwildclusterboot 0.3.0 Unreleased

• Additional performance improvements through parallelization. By default, boottest() uses half the available threads for parallel execution. The number of threads can be set via the nthreads function argument.
• Additional function arguments for boottest() - the user can now set the tolerance and maximum number of iterations for the calculation of confidence intervals. By default, tol = 1e-6 and maxiter = 10.
• The package no longer depends on data.table and fabricatr - both are now only suggested. Further, the package now comes with an example data set ‘voters’.

# fwildclusterboot 0.2.0 Unreleased

Add support for

• tests of two-sided, univariate hypotheses
• regression weights
• the subcluster bootstrap
• restricted (WCR) and unrestricted (WCU) bootstrap