NEWS.md
plot_nested
to use linewidth
instead of size
internally due to update to ggplot2
cmstatr_Validation
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.nested_data_plot
for producing nested data plots.hk_ext
cmstatr_Graphing
to show some examples of the use of nested_data_plot
.batch
to the carbon.data.2
example data set.k_factor_normal
, suppress warnings emitted by qt
when the non-central parameter is large.testthat
edition 3.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).override="all"
to allow overriding all applicable diagnostic tests that are automatically run by the basis_...
functions.na.rm
argument to cv
with identical behavior to the na.rm
argument of mean
and sd
.maximum_normed_residual
to fail with small data sets where all but two observations would be considered outliers.basis_...
functions), the error message now identifies which test produced the error.glance.equiv_mean_extremum
where it would include empty values when a sample was not specified.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
.glance.basis
to add diagnostic test results to resulting data.frame
print
methods for:
ad_ksample
anderson_darling
basis
equiv_mean_extremum
equiv_chage_mean
levene_test
maximum_normed_residual
alpha
into the mnr
object, and updated print
and glance
methods to show the value of alpha
specified by the uservapply
instead of sapply
to improve code safetytransform_mod_cv_2
to transform_mod_cv_ad
to better describe the purpose of this function.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.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.stat
extensions to ggplot2
:
stat_normal_surv_func
to plot a normal survival function based on the data givenstat_esf
to plot an empirical survival functiontransform_mod_cv
transform_mod_cv_2
normalize_group_mean
basis_nonparametric_large_sample
to basis_nonpara_large_sample
nonparametric_binomial_rank
to nonpara_binomial_rank