Releases: stefanocoretta/tidymv
Releases · stefanocoretta/tidymv
v3.4.2
v3.3.2
Developer
-
Use Roxygen 7.2.1.
-
Fix errors on CRAN related to HTML5 checks.
v3.3.1
Intention-to-deprecate notice
- tidymv will soon be deprecated, in favour of tidygam (https://github.com/stefanocoretta/tidygam). While development for tidygam is in progress, a notice of intention to deprecate is printed when the package is attached, so that users are warned.
Developer
-
Updated renv and packages.
-
Updated GitHub Action for pkgdown.
v3.3.0
Added
- Zenodo DOI in Readme.
Changed
predict_gam()
now has the extra argumenttype
, which allows the user to return the predicted values based on all terms or based on each term separately.
v3.2.1
Added
-
Use renv for development.
-
@return
roxygen entry added to all functions documentation. -
ci_z
argument inplot_difference()
.
Changed
- The output of
get_smooths_difference()
now includes agroup
column with a numeric index of significance blocks, so that plotting difference smooths with more than two alternating significance values is correct (seeplot-smooths
vignette, last example).
tidymv v3.2.0
Added
-
✨ -
get_smooths_difference()
which returns a tibble with the difference of two levels of a smooth (#11). -
🍇 -
plot-smooths.Rmd
now includes a plotting example withget_smooths_difference()
. -
👷 - Add GitHub actions for R CMD check.
-
🖼 - Add logo!
Changed
- ⬆️ - Use tidy evaluation.
Removed
- 🔥 - Travis CI has been removed (now use GitHub Actions).
tidymv v3.1.0
Added
-
reintroduced
plot_difference()
. -
imported code from itsadug for better integration with
plot_difference()
and compatibility with R 3.6.1. -
🍇 include example of
get_gam_predictions()
in plot smooths vignette.
Changed
get_gam_predictions()
now returns an.idx
column which assigns a number to each curve (when multiple variables are used). The.idx
column can be used to correctly groupgeom_ribbon()
for plotting CIs.
v3.0.0
3.0.0 - 2020-04-24
Removed
⚠️ BREAKING CHANGE!!! removeplot_difference()
due to the archiving of itsadug. To plot difference smooths, you can usemgcViz::plotDiff()
.
2.2.1 - 2020-04-22
Changed
- prevent error from
dplyr::lag()
when type of default is different (prepare for upcoming dplyr 1.0.0) - roxygen version 7.1.0
v2.2.0
Added
transform
argument inget_gam_predictions()
andplot_smooths()
(closes https://github.com/stefanocoretta/tidymv/issues/9)exlude_random
argument inplot_difference()
(it wasTRUE
by default and it was not possible to change it)- error message in
get_gam_predictions
when using discretised bam models andexclude_random = TRUE
(which is the default) - two example datasets to be used in the examples
- example of non-Gaussian GAM in
plot-smooths
vignette - support for models with non-syntactic column names (
log(y) ~ s(log(x))
)
Changed
- add option of setting values to
NULL
inpredict_gam()
when excluding terms to reduce computation time (also mentioned in the vignette) - improved performance of
get_gam_predictions()
when excluding terms - included mention to loaded packages in the vignettes
Fixed
- wrong examples in
plot_smooths()
andplot_difference()
(closes https://github.com/stefanocoretta/tidymv/issues/10) - handling of
s(bs = "re")
smooths
Removed
- import from cowplot (the function that required it has been removed)
v2.1.0
Added
- examples in documentation for all functions
Changed
- alpha of 0 line in difference smooth plot (now set to 0.5)
- prepared for CRAN first release
Fixed
- missing import in
plot_difference()
Deprecated
⚠️ time_series
is now deprecated and replaced withseries
.time_series
will be removed in future releases.
v2.0.0
Added
predict_gam()
to return a dataframe with all predictors and fitted values with standard errorgeom_smooth_ci()
which provides a newggplot2
geom
to conveniently plot smooths and confidence intervals from the output ofpredict_gam()
- vignette that illustrates how to use the new functions
- examples in the documentation
Changed
- name, arguments, and output of
create_event_start()
(>create_start_event()
, it breaks backward compatibility)
Removed
plot_gamsd()
(useplot_smooths()
andplot_difference()
)