R: Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation

# Functions and Utilities for Tidy Time Series Forecasting and Time Series Cross-Validation

## Documentation for package ‘tscv’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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