Version 0.10.0
- Updated documentation to clarify that the implementation of Levene’s
Test is based on median, which is also known as the Brown-Forsythe test.
Thanks to Brice Langston for pointing this out.
 
- Objects returned by the 
basis_...() methods now contain
the actual results of each diagnostic tests. This allows users to
interrogate any diagnostic failures. 
- Added 
condition_summary() methods for producing tables
that compare several environmental conditions. 
- Added the function 
geom_jitter_failure_mode() for
plotting data with multiple failure modes for some (or all)
observations. 
- Added a helper function for separating failure modes.
 
- Added a check in the 
maximum_normed_residual() test to
ensure that at least 3 observations were provided. 
- The 
calc_cv_star() function now accepts vectors. 
Version 0.9.3
- Updated 
basis_anova function to prevent division by
zero when MSE is 0 
- Update 
equiv_change_mean.print method so that
t-statistic and pooled SD are displayed. 
Version 0.9.2
- Update to Anderson Darling k-Sample vignette to explain differences
with SciPy implementation
 
- Updated README
 
- Update 
plot_nested to use linewidth
instead of size internally due to update to
ggplot2 
Version 0.9.1
- Updated tests to accommodate upcoming changes to the rlang package.
No change to test coverage was made.
 
Version 0.9.0
- Added the vignette 
cmstatr_Validation 
- Updated the expected value of the order statistic of a normally
distributed variable in the implementation of
hk_ext_z_j_opt. This affects the Basis values computed by
basis_hk_ext when method="optimum-order". Both
the new and old implementations appear to perform equally well. See the
vignette hk_ext for more information. 
- Added the function 
nested_data_plot for producing
nested data plots. 
- Added the vignette 
hk_ext 
- Updated the vignette 
cmstatr_Graphing to show some
examples of the use of nested_data_plot. 
- Added the additional column 
batch to the
carbon.data.2 example data set. 
- In 
k_factor_normal, suppress warnings emitted by
qt when the non-central parameter is large. 
- Updated the test to use 
testthat edition 3. 
Version 0.8.0
- Updated 
basis_anova so that in cases where the
between-batch variance is small compared with the within-batch variance,
a tolerance factor that doesn’t consider the structure of the data is
used. This matches the recommendation of Vangel (1992). 
- Added the alias 
override="all" to allow overriding all
applicable diagnostic tests that are automatically run by the
basis_... functions. 
- Improved documentation of diagnostic tests
 
- Added 
na.rm argument to cv with identical
behavior to the na.rm argument of mean and
sd. 
- Fixed bug causing 
maximum_normed_residual to fail with
small data sets where all but two observations would be considered
outliers. 
- When diagnostic tests produce an error (when automatically run by
the 
basis_... functions), the error message now identifies
which test produced the error. 
Version 0.7.1
- Fixed bug in 
glance.equiv_mean_extremum where it would
include empty values when a sample was not specified. 
- Moved 
dplyr from Suggests to Depends. It is expected
that nearly all users will use this package in their workflow, and a
future version of cmstatr will also rely on functionality
from dplyr. 
- Changed tests and vignettes such that tests and vignette code is not
re-run when the necessary packages are not available. Test coverage and
re-building of vignettes is unchanged when all packages in Depends and
Suggests are available.
 
Version 0.7.0
- Added optional argument to 
glance.basis to add
diagnostic test results to resulting data.frame 
Version 0.6.0
- Improved the documentation for several functions
 
- Made minor formatting changes to the 
print methods for:
ad_ksample 
anderson_darling 
basis 
equiv_mean_extremum 
equiv_chage_mean 
levene_test 
maximum_normed_residual 
 
- Added 
alpha into the mnr object, and
updated print and glance methods to show the
value of alpha specified by the user 
Version 0.5.2
- Internally use 
vapply instead of sapply to
improve code safety 
- Increased coverage of unit tests
 
Version 0.5.1
- Fixed the title of the graphing vignette
 
Version 0.5.0
- Renamed 
transform_mod_cv_2 to
transform_mod_cv_ad to better describe the purpose of this
function. 
- Removed the optional argument from 
transform_mod_cv.
Now if several groups are to be transformed separately, this needs to be
done explicitly using dplyr::group_by or a similar
strategy. 
- Fixed bug related to the automated diagnostic tests of pooled basis
methods when 
modcv = TRUE. Previously, the diagnostic tests
were performed with the unmodified data. After this bug fix, the the
data after the modified CV transform is used for the diagnostic
tests. 
- Added 
stat extensions to ggplot2:
stat_normal_surv_func to plot a normal survival
function based on the data given 
stat_esf to plot an empirical survival function 
 
- Updated cmstatr_Tutorial vignette
 
- Created cmstatr_Graphing vignette
 
- Various documentation improvements
 
Version 0.4.0
- Added automated diagnostic tests to basis_… methods
 
- Updated argument names for functions:
transform_mod_cv 
transform_mod_cv_2 
normalize_group_mean 
 
- Updated cmstatr_Tutorial vignette
 
Version 0.3.0
- Added modified CV functionality
 
- Added glance and augment methods for most objects
 
- Added function for calculating CV of a sample
 
- Breaking changes:
- Renamed function 
basis_nonparametric_large_sample to
basis_nonpara_large_sample 
- Renamed function 
nonparametric_binomial_rank to
nonpara_binomial_rank 
 
Version 0.2.0
- Added ANOVA basis calculation
 
- Added non-parametric basis calculations
 
Version 0.1.0