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

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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