A B D F G H I L M P R S T W misc
add_time | Add / Subtract (For Time Series) |
auto_lambda | Box Cox Transformation |
between_time | Between (For Time Series): Range detection for date or date-time sequences |
bike_sharing_daily | Daily Bike Sharing Data |
box_cox_inv_vec | Box Cox Transformation |
box_cox_vec | Box Cox Transformation |
diff_inv_vec | Differencing Transformation |
diff_vec | Differencing Transformation |
filter_by_time | Filter (for Time-Series Data) |
fourier_vec | Fourier Series |
get_tk_time_scale_template | Get and modify the Time Scale Template |
has_timetk_idx | Extract an index of date or datetime from time series objects, models, forecasts |
impute_ts_vec | Missing Value Imputation for Time Series |
lag_vec | Lag Transformation |
m4_daily | Sample of 4 Daily Time Series Datasets from the M4 Competition |
m4_hourly | Sample of 4 Hourly Time Series Datasets from the M4 Competition |
m4_monthly | Sample of 4 Monthly Time Series Datasets from the M4 Competition |
m4_quarterly | Sample of 4 Quarterly Time Series Datasets from the M4 Competition |
m4_weekly | Sample of 4 Weekly Time Series Datasets from the M4 Competition |
m4_yearly | Sample of 4 Yearly Time Series Datasets from the M4 Competition |
pad_by_time | Insert time series rows with regularly spaced timestamps |
plot_acf_diagnostics | Visualize the ACF, PACF, and CCFs for One or More Time Series |
plot_seasonal_diagnostics | Visualize Multiple Seasonality Features for One or More Time Series |
plot_stl_diagnostics | Visualize STL Decomposition Features for One or More Time Series |
plot_time_series | Interactive Plotting for One or More Time Series |
plot_time_series_cv_plan | Visualize a Time Series Resample Plan |
roll_apply_vec | Rolling Window Transformation |
set_tk_time_scale_template | Get and modify the Time Scale Template |
slidify | Create a rolling (sliding) version of any function |
smooth_vec | Smoothing Transformation using Loess |
step_box_cox | Box-Cox Transformation using Forecast Methods |
step_diff | Create a differenced predictor |
step_fourier | Fourier Features for Modeling Seasonality |
step_holiday_signature | Holiday Feature (Signature) Generator |
step_impute_ts | Imputation for Time Series using Forecast Methods |
step_roll_apply | Rolling Window Transformation |
step_smooth | Smoothing Transformation using Loess |
step_timeseries_signature | Time Series Feature (Signature) Generator |
subtract_time | Add / Subtract (For Time Series) |
summarise_by_time | Summarise (for Time Series Data) |
summarize_by_time | Summarise (for Time Series Data) |
taylor_30_min | Half-hourly electricity demand |
tidy.step_box_cox | Box-Cox Transformation using Forecast Methods |
tidy.step_diff | Create a differenced predictor |
tidy.step_fourier | Fourier Features for Modeling Seasonality |
tidy.step_holiday_signature | Holiday Feature (Signature) Generator |
tidy.step_impute_ts | Imputation for Time Series using Forecast Methods |
tidy.step_roll_apply | Rolling Window Transformation |
tidy.step_smooth | Smoothing Transformation using Loess |
tidy.step_timeseries_signature | Time Series Feature (Signature) Generator |
timetk | timetk: a toolkit for time series |
timetk_internal | Internal Functions Used in timetk |
time_arithmetic | Add / Subtract (For Time Series) |
time_series_cv | Time Series Cross Validation |
tk_acf_diagnostics | Group-wise ACF, PACF, and CCF Data Preparation |
tk_augment_differences | Add many differenced columns to the data |
tk_augment_fourier | Add many fourier series to the data |
tk_augment_holiday | Add many holiday features to the data |
tk_augment_holiday_signature | Add many holiday features to the data |
tk_augment_lags | Add many lags to the data |
tk_augment_roll_apply | Add many rolling window calculations to the data |
tk_augment_timeseries | Add many time series features to the data |
tk_augment_timeseries_signature | Add many time series features to the data |
tk_get_frequency | Automatic frequency and trend calculation from a time series index |
tk_get_holiday | Get holiday features from a time-series index |
tk_get_holidays_by_year | Get holiday features from a time-series index |
tk_get_holiday_signature | Get holiday features from a time-series index |
tk_get_timeseries | Get date features from a time-series index |
tk_get_timeseries_signature | Get date features from a time-series index |
tk_get_timeseries_summary | Get date features from a time-series index |
tk_get_timeseries_unit_frequency | Get the timeseries unit frequency for the primary time scales |
tk_get_timeseries_variables | Get date or datetime variables (column names) |
tk_get_trend | Automatic frequency and trend calculation from a time series index |
tk_index | Extract an index of date or datetime from time series objects, models, forecasts |
tk_make_future_timeseries | Make future time series from existing |
tk_make_holiday_sequence | Make daily Holiday and Weekend date sequences |
tk_make_timeseries | Intelligent date and date-time sequence creation |
tk_make_weekday_sequence | Make daily Holiday and Weekend date sequences |
tk_make_weekend_sequence | Make daily Holiday and Weekend date sequences |
tk_seasonal_diagnostics | Group-wise Seasonality Data Preparation |
tk_stl_diagnostics | Group-wise STL Decomposition (Season, Trend, Remainder) |
tk_stl_diagnostics.data.frame | Group-wise STL Decomposition (Season, Trend, Remainder) |
tk_summary_diagnostics | Group-wise Time Series Summary |
tk_tbl | Coerce time-series objects to tibble. |
tk_time_scale_template | Get and modify the Time Scale Template |
tk_time_series_cv_plan | Time Series Resample Plan Data Preparation |
tk_ts | Coerce time series objects and tibbles with date/date-time columns to ts. |
tk_ts_ | Coerce time series objects and tibbles with date/date-time columns to ts. |
tk_ts_.data.frame | Internal Functions Used in timetk |
tk_ts_.default | Internal Functions Used in timetk |
tk_xts | Coerce time series objects and tibbles with date/date-time columns to xts. |
tk_xts_ | Coerce time series objects and tibbles with date/date-time columns to xts. |
tk_zoo | Coerce time series objects and tibbles with date/date-time columns to xts. |
tk_zooreg | Coerce time series objects and tibbles with date/date-time columns to ts. |
tk_zooreg_ | Coerce time series objects and tibbles with date/date-time columns to ts. |
tk_zooreg_.data.frame | Internal Functions Used in timetk |
tk_zooreg_.default | Internal Functions Used in timetk |
tk_zoo_ | Coerce time series objects and tibbles with date/date-time columns to xts. |
walmart_sales_weekly | Sample Time Series Retail Data from the Walmart Recruiting Store Sales Forecasting Competition |
wikipedia_traffic_daily | Sample Daily Time Series Data from the Web Traffic Forecasting (Wikipedia) Competition |
%+time% | Add / Subtract (For Time Series) |
%-time% | Add / Subtract (For Time Series) |