None
util_log_ts()
util_singlediff_ts()
util_doublediff_ts()
util_difflog_ts()
util_doubledifflog_ts()
ts_growth_rate_vec()
auto_stationarize()
ts_auto_arima()
to utilize the parsnip engine of auto_arima
if .tune
is set to FALSE
None
ts_growth_rate_vec()
ts_adf_test()
auto_stationarize()
ts_growth_rate_augment()
.true
param to FALSE
None
None
None
None
tune::show_best(n = 1)
instead of Inf
and using dplyr::slice(1)
None
ts_ma_plt()
errors stemming from deprecations. Also fixed examples of all boilerplate functions.None
ts_geometric_brownian_motion()
ts_brownian_motion_augment()
ts_geometric_brownian_motion_augment()
ts_brownian_motion_plot()
ts_brownian_motion()
49x speedup by way of vectorization..motion_type
ts_vva_plot()
None
ts_brownian_motion()
ts_scedacity_scatter_plot()
None
None
ts_lag_correlation()
to fix a bug in the correlation matrix calculation where columns may come through that are not numeric and are not part of the original value and it’s lags.None
None
recipes::check_type()
on recipe functions.ts_model_spec_tune_template()
to set regression
as the argument to parsnip::set_mode()
which fires a failure in the ts_model_auto_tune()
not running on newer versions of parsnip
None
ts_wfs_xgboost()
ts_calendar_heatmap_plot()
Change weekdays and Monthls to abbreviated labels.ts_sma_plot()
There is a change in the API of this function. It now requires a data.frame
/tibble
to be passed to the .data
parameter, and it also now requires the input of a date column and value column. This also now no longer returns invisible. There was also a fix in the sliding calculation to appropriately use the given value column.ts_extract_auto_fitted_workflow()
Which will pull out the fitted workflow from any of the Boilerplate functions.ts_auto_lm()
by dropping step_rm()
and step_corr()
which would prevent calibrate_and_plot()
from working due to modeltime_calibration()
failing. Also dropped unused parameters from function and documentation.ts_lag_correlation()
select
statement.None
ts_time_event_analysis_tbl()
ts_lag_correlation()
ci_hi()
and ci_lo()
ts_event_analysis_plot()
ts_model_auto_tune()
and ts_model_spec_tune_template()
to accept svm_poly
and svm_rbf
. This helps in allowing users to auto tune models that are create by ts_wfs_svm_poly()
and ts_wfs_svm_rbf()
functions respectively. Also added “model_spec_class” to the output of the ts_model_auto_tune()
function.None
ts_auto_arima()
boiler plate function.color_blind()
ts_scale_fill_colorblind()
and ts_scale_color_colorblind()
ts_auto_smooth_es()
ts_auto_theta()
ts_auto_lm()
ts_auto_svm_poly()
ts_auto_svm_rbf()
ts_auto_arima_xgboots()
when .tune
is FALSE.tune::tune()
healthyR
to healthyR.ai
in anticipation of dropping kmeans
functionality from healthyR
None
ts_arima_simulator()
ts_feature_cluster()
ts_feature_cluster_plot()
ts_auto_glmnet()
ts_auto_xgboost()
ts_auto_arima_xgboost()
ts_auto_mars()
ts_auto_exp_smoothing()
ts_auto_croston()
ts_auto_nnetar()
ts_auto_prophet_reg()
ts_auto_prophet_boost()
[recipes::print_step()]
method.ggplot2::theme_minimal()
hardhat
to DESCRIPTION since functionality like extracting dials parameters was taken out of dials and moved to hardhat.None
ts
and Fitted tibble
data to output.ts
and Residuals tibble
data to output.Arima()
models with xreg to ts_forecast_simulator()
model_extraction_helper()
to utilize forecast:::arima.string()
under the hood for Arima
arima
and auto.arima
models produced by the forecast
package.crayon
, cli
, and rstudioapi
since all it did was make a welcome message that can be done with regular print()
method.None
ts_qq_plot()
ts_scedacity_scatter_plot()
ts_model_rank_tbl()
model_extraction_helper()
to grab workflow
model_spec
and model_fit
objects.None
ts_vva_plot()
ts_model_compare()
ts_acceleration_vec()
ts_acceleration_augment()
step_ts_acceleration()
ts_velocity_vec()
ts_velocity_augment()
step_ts_velocity()
.date_col
to ts_sma_plot()
so that if a tibble is passed the appropriate column is passed to the ggplot
object.model_extraction_helper()
function to extract workflow fit models.None
None
Fix #143 - Drop mtry = tune::tune()
from ts_model_spec_tune_template
as it causes issues downstream.
None
tidy_fft()
functionts_info_tbl()
functionts_sma_plot()
functionts_to_tbl()
functionts_model_auto_tune()
functionts_model_spec_tune_template()
functionts_wfs_auto_arima()
functionts_wfs_arima_boost()
functionts_wfs_ets_reg()
functionts_wfs_nnetar_reg()
functionts_wfs_prophet_reg()
functionts_auto_recipe()
bug that forced the change of column names in the output. This has been fixed and the column names supplied will now be in the recipe terms.None
ts_forecast_simulator()
functioncalibrate_and_plot()
helper functionts_wfs_lin_reg()
, ts_wfs_mars()
, ts_wfs_svm_poly()
, ts_wfs_svm_rbf()
model_extraction_helper()
helper functionts_ma_plot()
plotting functionts_calendar_heatmap_plot()
plotting functionts_splits_plot()
plotting functionNone
ts_auto_recipe()
functionNone
NEWS.md
file to track changes to the package.