Changes in version 0.2.1                        

  - Fixed a warning ("Unknown or uninitialised column: weight.scale")
    that appeared when using bootstrap.estimates() with
    rescaled.bootstrap.sample(): the index column was being extracted as
    a one-column tibble instead of a plain vector, causing tibble's $
    accessor to misreport the column as missing
  - Fixed a deprecation warning from rlang ("Unquoting language objects
    with !!! is deprecated"): replaced !!!psu.vars with
    across(all_of(...)) / all_of(...) throughout
    rescaled.bootstrap.sample() and get.rescaled.bootstrap.weights()
  - Fixed rescaled.bootstrap.weights() producing column names
    boot_weight_rep.1, boot_weight_rep.2, … instead of the documented
    boot_weight_1, boot_weight_2, …
  - Added vignette "The rescaled bootstrap" illustrating the main
    workflow with the MU284 example data
  - Added pkgdown site
  - rescaled.bootstrap.sample() and get.rescaled.bootstrap.weights() now
    issue a warning when any stratum contains fewer than 2 PSUs
    (variance cannot be estimated in that case; bootstrap weights for
    the stratum will be 0)
  - Added regression tests covering the above bug fixes and the
    single-PSU warning

                        Changes in version 0.2.0                        

  - Added get.rescaled.bootstrap.weights(): new function that returns
    rescaled bootstrap weights (and optionally cluster counts and
    scaling factors) in a wide data frame, making it straightforward to
    use the rescaled bootstrap for jackknife-after-bootstrap (JAB)
    variance estimation
  - rescaled.bootstrap.sample() gains an include_cc argument; when TRUE
    it returns per-rep cluster inclusion counts alongside the
    weight-scaling factors, which are needed for JAB calculations
  - Fixed a bug where bootstrap.estimates() failed silently when used
    with rescaled.bootstrap.sample(): the weight-scaling column was
    named weight_scale (underscore) in the sampler but read as
    weight.scale (dot) by the estimator, causing weights to collapse to
    numeric(0) and all estimates to be NaN / Inf
  - Expanded test suite: added structural and semantic tests for
    rescaled.bootstrap.sample(), srs.bootstrap.sample(),
    get.rescaled.bootstrap.weights(), and rescaled.bootstrap.weights();
    added a regression test that directly catches the weight.scale
    naming bug; added tests for the weighted.mean() helper

                     Changes in version 0.1.0.9000                      

                 Changes in version 0.0.3 (2023-01-09)                  

  - fixed some dependency errors that suddenly arose (explicitly use
    plyr:: in a few places)
  - dropped now-deprecated group_indices_() in favor of
    cur_group_index()
  - changed docs to use Markdown roxygen
  - added MU284 dataset for examples and tests
  - added examples to exported function docs

                        Changes in version 0.0.2                        

  - moved unit tests for goc and helper functions in from
    networkreporting
  - added rescaled.bootstrap.weights helper function for case when a
    tibble with all of the rescaled bootstrap weights is useful
  - added dependencies to tidyverse, magrittr, and purrr

                 Changes in version 0.0.1 (2016-05-02)                  

  - first CRAN version, May 2016