Man pages for tscv
Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation
| acf_vec | Estimate autocorrelations of a numeric vector |
| check_data | Check and prepare tsibble data |
| DSHW | Double Seasonal Holt-Winters model |
| elec_load | Hourly electricity load (actual values and forecasts) |
| elec_price | Hourly day-ahead electricity spot prices |
| estimate_acf | Estimate autocorrelations by time series |
| estimate_kurtosis | Estimate kurtosis |
| estimate_mode | Estimate the mode of a distribution |
| estimate_pacf | Estimate partial autocorrelations by time series |
| estimate_skewness | Estimate skewness |
| fitted.DSHW | Extract fitted values from a DSHW model |
| fitted.MEDIAN | Extract fitted values from a median model |
| fitted.SMEAN | Extract fitted values from a seasonal mean model |
| fitted.SMEDIAN | Extract fitted values from a seasonal median model |
| fitted.SNAIVE2 | Extract fitted values from a SNAIVE2 model |
| fitted.TBATS | Extract fitted values from a TBATS model |
| forecast.DSHW | Forecast a DSHW model |
| forecast.MEDIAN | Forecast a median model |
| forecast.SMEAN | Forecast a seasonal mean model |
| forecast.SMEDIAN | Forecast a seasonal median model |
| forecast.SNAIVE2 | Forecast a SNAIVE2 model |
| forecast.TBATS | Forecast a TBATS model |
| interpolate_missing | Interpolate missing values |
| M4_monthly_data | Monthly time series data from the M4 Competition |
| M4_quarterly_data | Quarterly time series data from the M4 Competition |
| mae_vec | Calculate the mean absolute error |
| make_accuracy | Estimate point forecast accuracy |
| make_errors | Calculate forecast errors and percentage errors |
| make_future | Convert forecasts to a future frame |
| make_split | Create train-test splits for time series cross-validation |
| make_tsibble | Convert data to a tsibble |
| mape_vec | Calculate the mean absolute percentage error |
| MEDIAN | Median model |
| me_vec | Calculate the mean error |
| model_sum.DSHW | Summarize a DSHW model |
| model_sum.MEDIAN | Summarize a median model |
| model_sum.SMEAN | Summarize a seasonal mean model |
| model_sum.SMEDIAN | Summarize a seasonal median model |
| model_sum.SNAIVE2 | Summarize a SNAIVE2 model |
| model_sum.TBATS | Summarize a TBATS model |
| mpe_vec | Calculate the mean percentage error |
| mse_vec | Calculate the mean squared error |
| pacf_vec | Estimate partial autocorrelations of a numeric vector |
| plot_bar | Plot data as a bar chart |
| plot_density | Plot a kernel density estimate |
| plot_histogram | Plot data as a histogram |
| plot_line | Plot data as a line chart |
| plot_point | Plot data as a scatterplot |
| plot_qq | Create a quantile-quantile plot |
| residuals.DSHW | Extract residuals from a DSHW model |
| residuals.MEDIAN | Extract residuals from a median model |
| residuals.SMEAN | Extract residuals from a seasonal mean model |
| residuals.SMEDIAN | Extract residuals from a seasonal median model |
| residuals.SNAIVE2 | Extract residuals from a SNAIVE2 model |
| residuals.TBATS | Extract residuals from a TBATS model |
| rmse_vec | Calculate the root mean squared error |
| scale_color_tscv | Create a tscv color scale |
| scale_fill_tscv | Create a tscv fill scale |
| slice_test | Slice test data from a split frame |
| slice_train | Slice training data from a split frame |
| smape_vec | Calculate the symmetric mean absolute percentage error |
| SMEAN | Seasonal mean model |
| SMEDIAN | Seasonal median model |
| smooth_outlier | Identify and replace outliers |
| SNAIVE2 | Seasonal naive model with weekday-specific lags |
| split_index | Create indices for train and test splits |
| summarise_data | Summarise time series data |
| summarise_split | Summarise train-test splits |
| summarise_stats | Summarise distributional statistics by time series |
| TBATS | TBATS model |
| theme_tscv | Custom ggplot2 theme for tscv |
| tscv_cols | Extract tscv colors |
| tscv_pal | Create a tscv color palette |
