Maintenance release to accommodate breaking changes in dplyr 1.1.0.
This first major release accompanies the publication of an article in the Journal of Statistical Software:
Vasilopoulos, K., Pavlidis, E., & Martínez-García, E. (2022). exuber: Recursive Right-Tailed Unit Root Testing with R. Journal of Statistical Software, 103(1), 1–26. https://doi.org/10.18637/jss.v103.i10
-
New arg
trunc
-
Fixed inconsistencies among functions.
-
Now radf stores the data that are later can be accessed with
mat
+ -
Advanced features on datestamping: New columns that indicate:
- Signal
- Peak
- Ongoing
- Nonrejected
-
New datestamping procedure
rev_radf
etc. -
New bootstrap procedure
radf_wb_cv2
andradf_wb_distr2
-
New coloring convention for plotting
ds
andobj
classes
- Now autoplot can include periods that have an ongoing bubble
- Include printing methods for
radf_obj
andradf_cv
. - Removed unused class definitions.
- Using
progress
package for progress_bar.
Maintenance release for compatibility with dplyr v1.0.0.
We have the following design in mind for future scalability. If you want make inference about radf
models, then the estimation can be achieved with radf()
function and return an object of class radf_obj
, and the critical values can be achieved with radf_*_cv()
and return an object of class radf_cv
.
autoplot()
forradf
models has been refactored and new features have been added for more flexibility and conformity with the {ggplot} mindset.- Because of the change in
autoplot
,ggarrange()
is now defunct. fortify()
methods have been replaced bytidy()
,augment()
,tidy_join()
andglance_join()
methods.fortify()
methods are now defunct.- Also
glance()
is now defunct. The user can usetidy()
withpanel=TRUE
instead. - Changed the names of:
mc_cv()
toradf_mc_cv()
.mc_cv()
is now deprecated.mc_distr()
toradf_mc_distr()
.mc_distr()
is now deprecated.wb_cv()
toradf_wb_cv()
.wb_cv()
is now deprecated.wb_distr()
toradf_wb_distr()
.wb_distr()
is now deprecated.sb_cv()
toradf_sb_cv()
.sb_cv()
is now deprecated.sb_distr()
toradf_sb_distr()
.sb_distr()
is now deprecated.crit
dataset toradf_crit
.col_names()
toseries_names()
.col_names()
is now deprecated.
- We created a new package called
exuberdata
that accommodates critical values for up to 2000 observations. Critical values can be examined withexuberdata::radf_crit2
. The package is created throughdrat
R archive Template, and can be easily installed withinstall.packages('exuberdata', repos = 'https://kvasilopoulos.github.io/drat/', type = 'source')
or throughinstall_exuberdata
wrapper function that is provided inexuber
.
- The package
zoo
has been used as a dependency to import the methodindex()
. We made the decision to removezoo
and create a new methodindex()
internally.
- Changed
opt_bsadf = conservative
for the simulated critical values (crit
), also reduced the size of thecrit
from 700 to 600 due to package size restrictions. sim_dgp1()
andsim_dgp2()
have been renamed tosim_psy1()
andsim_psy2()
to better describe the origination of the dgp.sim_dgp1()
andsim_dgp2()
have been soft-deprecated.autoplot_radf()
arranges automatically multiple graphs, to return to previous behavior we included the optional argumentarrange
which is set to TRUE by default.
Three new functions have been added to simulate empirical distributions for:
mc_dist()
: Monte Carlowb_dist()
: Wild Bootstrapsb_dist()
: Sieve Bootstrap
and a function that can calculate the p-values calc_pvalue()
given the above
distributions as argument.
Also methods tidy()
and autoplot()
have been added to turn the object into
a tidy tibble and draw a particular plot with ggplot2, respectively.
tidy()
methods for objects of classradf
,cv
.augment()
methods for objects of classradf
andcv
.augment_join()
to combine objectradf
andcv
into a single data.frame.glance()
method for objects of classradf
.
- New printing output for the functions
summary()
,diagnostics()
anddatestamp()
. - New improved progressbar with more succinct printing for
wb_cv()
seed
argument to functions that are using rng. Also the option to declare a global seed for reproducibility with theoption(exuber.global_seed = ###)
sb_cv()
andwb_cv()
now can parse data that contain a date-column. Similarly, to whatradf()
is doing.
- Website development
- Changed DESCRIPTION to include
sb_cv
reference. - Renamed boolean to dummy from
datestamp
anddiagnostics
. datestamp
dummy is now an attribute.
Some of the arguments in the functions were included as options, you can
set the package options with e.g. options(exuber.show_progress = TRUE)
.
parallel
option boolean, allows for parallel in critical values computation.ncores
option numeric, sets the number of cores, defaults to max - 1.show_progress
option boolean, allows you to disable the progress bar, defaults to TRUE.
- Panel estimation in
radf()
- Added
sb_cv()
function: Panel Sieve Bootstrapped critical values - Default critical values are supplied directly into
summary()
,diagnostics
,datestamp()
andautoplot()
, without having to specify argument cv. The critical values have been simulated frommc_cv()
function and stored as data. Custom critical values should be provided by the user with the optioncv
. - Added
ggarrange()
function, that can arrange a list of ggplot objects into a single grob. - Added
fortify
to arrange a data.frame fromradf()
function.
- Parallel and ncores arguments are now set as options.
- Ability to remove progressbar from package options.
radf()
can parse date fromts
objects.report()
has been renamed intosummary()
.plot()
has been renamed intoautoplot()
.plot()
andreport()
are soft deprecated.
- Progressbar appears in the beginning of the iteration
- Plotting date now works without having to to include any additional plotting option