Changes in version 1.0.17 (2022-11-16)                 

  - Maintenance update:
      - minor fix in vignettes to remove CRAN errors due to suggested
        package not available.

                 Changes in version 1.0.16 (2020-02-04)                 

  - Maintenance update:
      - minor fix in se_boot() to remove CRAN warning.

                 Changes in version 1.0.15 (2019-08-19)                 

  - Maintenance update:
      - minor fix in imported packages to remove NOTE in CRAN checks.
      - Updated DESCRIPTION with links to published work.

                 Changes in version 1.0.14 (2019-08-02)                 

  - CAISEr plotting now returns a list of ggplot objects and relevant
    dataframes, and plots a nested plot of relevant information.
  - fixed bug when running experiment with two algorithms (due to the
    default drop = TRUE when subsetting rows in se_param()/se_boot()).

                        Changes in version 1.0.6                        

  - Added plot function to class CAISEr

                 Changes in version 1.0.5 (2019-07-13)                  

  - Major update: package can now deal with comparisons of multiple (>2)
    algorithms. This version is not backward compatible with
    versions 0.xx. To use the previous versions (e.g., to replicate the
    results from the paper "Sample Size Estimation for Power and
    Accuracy in the Experimental Comparison of Algorithms", Journal of
    Heuristics 2019), install the previous version from
    https://cran.r-project.org/src/contrib/CAISEr_0.3.3.tar.gz.
  - Replaced function calc_nreps2() by calc_nreps() to calculate the
    number of repetitions in the case of multiple (>2) algorithms.
  - function calc_se() now performs point estimate and standard error
    calculations for all pairs of interest in the case of multiple
    algorithms.
  - function calc_instances() now returns the number of required
    instances to maintain the desired power for the family of
    experiments, based on Holm's step-down correction. It also returns
    the sequence of alpha values and the corresponding power to detect
    the effect size d, for each comparison using Holm's method.
  - Removed class CAISER_powercurve and all associated methods (print,
    summary, plot) as these were (very) rarely used.
  - Added class nreps with new summary/plotting functions.
  - Updated print and summary methods.
  - The package now supports saving and (re)loading partially executed
    experiments.

                 Changes in version 0.3.3 (2018-07-24)                  

  - fixed problem with printing version in the vignette.

                        Changes in version 0.3.2                        

  - fixed rare bug in calc_se() that resulted in NaN if two vectors with
    the same sample mean and same sample variance were passed as
    arguments.

                        Changes in version 0.3.1                        

  - Added function to consolidate partial results saved to file
    (consolidate.partial.results())
  - Minor improvements to saving partial results to file: users can now
    select arbitrary directory for saving

                         Changes in version 0.3                         

  - run_experiment() can now be run in parallel using multiple cores.
  - run_experiment() and calc_nreps2() can now save results to files.

                        Changes in version 0.2.4                        

  - run_experiment() now forces the use of all available instances if
    power >= 1.

                        Changes in version 0.2.3                        

  - Improved plot and summary functions for CAISErPowercurve objects.
  - Added options to calc_power_curve() to determine the range of effect
    sizes to consider.

                        Changes in version 0.2.2                        

  - Added new example and use case to calc_nreps2()

                 Changes in version 0.2.1 (2017-10-29)                  

  - Minor fixes, particularly in printing function.

                        Changes in version 0.2.0                        

  - Initial release on CRAN.