Man pages for timetk
A Tool Kit for Working with Time Series
| anomalize | Automatic group-wise Anomaly Detection |
| between_time | Between (For Time Series): Range detection for date or... |
| bike_sharing_daily | Daily Bike Sharing Data |
| box_cox_vec | Box Cox Transformation |
| condense_period | Convert the Period to a Lower Periodicity (e.g. Go from Daily... |
| diff_vec | Differencing Transformation |
| FANG | Stock prices for the "FANG" stocks. |
| filter_by_time | Filter (for Time-Series Data) |
| filter_period | Apply filtering expressions inside periods (windows) |
| fourier_vec | Fourier Series |
| future_frame | Make future time series from existing |
| is_date_class | Check if an object is a date class |
| lag_vec | Lag Transformation |
| log_interval_vec | Log-Interval Transformation for Constrained Interval... |
| m4_daily | Sample of 4 Daily Time Series Datasets from the M4... |
| m4_hourly | Sample of 4 Hourly Time Series Datasets from the M4... |
| m4_monthly | Sample of 4 Monthly Time Series Datasets from the M4... |
| m4_quarterly | Sample of 4 Quarterly Time Series Datasets from the M4... |
| m4_weekly | Sample of 4 Weekly Time Series Datasets from the M4... |
| m4_yearly | Sample of 4 Yearly Time Series Datasets from the M4... |
| mutate_by_time | Mutate (for Time Series Data) |
| normalize_vec | Normalize to Range (0, 1) |
| pad_by_time | Insert time series rows with regularly spaced timestamps |
| parse_date2 | Fast, flexible date and datetime parsing |
| plot_acf_diagnostics | Visualize the ACF, PACF, and CCFs for One or More Time Series |
| plot_anomalies | Visualize Anomalies for One or More Time Series |
| plot_anomaly_diagnostics | Visualize Anomalies for One or More Time Series |
| plot_seasonal_diagnostics | Visualize Multiple Seasonality Features for One or More Time... |
| plot_stl_diagnostics | Visualize STL Decomposition Features for One or More Time... |
| plot_time_series | Interactive Plotting for One or More Time Series |
| plot_time_series_boxplot | Interactive Time Series Box Plots |
| plot_time_series_cv_plan | Visualize a Time Series Resample Plan |
| plot_time_series_regression | Visualize a Time Series Linear Regression Formula |
| required_pkgs.timetk | S3 methods for tracking which additional packages are needed... |
| slice_period | Apply slice inside periods (windows) |
| slidify | Create a rolling (sliding) version of any function |
| slidify_vec | Rolling Window Transformation |
| smooth_vec | Smoothing Transformation using Loess |
| standardize_vec | Standardize to Mean 0, Standard Deviation 1 (Center & Scale) |
| 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_log_interval | Log Interval Transformation for Constrained Interval... |
| step_slidify | Slidify Rolling Window Transformation |
| step_slidify_augment | Slidify Rolling Window Transformation (Augmented Version) |
| step_smooth | Smoothing Transformation using Loess |
| step_timeseries_signature | Time Series Feature (Signature) Generator |
| step_ts_clean | Clean Outliers and Missing Data for Time Series |
| step_ts_impute | Missing Data Imputation for Time Series |
| step_ts_pad | Pad: Add rows to fill gaps and go from low to high frequency |
| summarise_by_time | Summarise (for Time Series Data) |
| taylor_30_min | Half-hourly electricity demand |
| tidyeval | Tidy eval helpers |
| time_arithmetic | Add / Subtract (For Time Series) |
| time_series_cv | Time Series Cross Validation |
| time_series_split | Simple Training/Test Set Splitting for Time Series |
| timetk-package | timetk: Time Series Analysis in the Tidyverse |
| tk_acf_diagnostics | Group-wise ACF, PACF, and CCF Data Preparation |
| tk_anomaly_diagnostics | Automatic group-wise Anomaly Detection by STL Decomposition |
| 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_lags | Add many lags to the data |
| tk_augment_slidify | Add many rolling window calculations to the data |
| tk_augment_timeseries | Add many time series features to the data |
| tk_get_frequency | Automatic frequency and trend calculation from a time series... |
| tk_get_holiday | Get holiday features from a time-series index |
| tk_get_timeseries | 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_index | Extract an index of date or datetime from time series... |
| 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_seasonal_diagnostics | Group-wise Seasonality Data Preparation |
| tk_stl_diagnostics | 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... |
| tk_ts_dispatch_ | S3 methods for ts method dispatch |
| tk_tsfeatures | Time series feature matrix (Tidy) |
| tk_xts | Coerce time series objects and tibbles with date/date-time... |
| tk_zoo | Coerce time series objects and tibbles with date/date-time... |
| tk_zooreg | Coerce time series objects and tibbles with date/date-time... |
| tk_zooreg_dispatch_ | S3 methods for zooreg method dispatch |
| ts_clean_vec | Replace Outliers & Missing Values in a Time Series |
| ts_impute_vec | Missing Value Imputation for Time Series |
| walmart_sales_weekly | Sample Time Series Retail Data from the Walmart Recruiting... |
| wikipedia_traffic_daily | Sample Daily Time Series Data from the Web Traffic... |
