R: Core Tools for Packages in the 'fable' Framework

# Core Tools for Packages in the 'fable' Framework

## Documentation for package ‘fabletools’ version 0.7.0

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

## Help Pages

A B C D E F G H I M N O P Q R S T W

fabletools-package | fabletools: Core Tools for Packages in the 'fable' Framework

## -- A --

accuracy.fbl_ts | Evaluate accuracy of a forecast or model
accuracy.mdl_df | Evaluate accuracy of a forecast or model
accuracy.mdl_ts | Evaluate accuracy of a forecast or model
ACF1 | Point estimate accuracy measures
aggregate_index | Expand a dataset to include temporal aggregates
aggregate_key | Expand a dataset to include other levels of aggregation
agg_vec | Create an aggregation vector
as_dable | Coerce to a dable object
as_dable.tbl_df | Coerce to a dable object
as_dable.tbl_ts | Coerce to a dable object
as_fable | Coerce to a fable object
as_fable.fbl_ts | Coerce to a fable object
as_fable.forecast | Coerce to a fable object
as_fable.grouped_df | Coerce to a fable object
as_fable.grouped_ts | Coerce to a fable object
as_fable.tbl_df | Coerce to a fable object
as_fable.tbl_ts | Coerce to a fable object
as_mable | Coerce a dataset to a mable
as_mable.data.frame | Coerce a dataset to a mable
augment.mdl_df | Augment a mable
augment.mdl_lst | Augment a mable
augment.mdl_ts | Augment a mable
autolayer.fbl_ts | Plot a set of forecasts
autolayer.tbl_ts | Plot time series from a tsibble
autoplot.dcmp_ts | Decomposition plots
autoplot.fbl_ts | Plot a set of forecasts
autoplot.tbl_ts | Plot time series from a tsibble

## -- B --

bottom_up | Bottom up forecast reconciliation
box_cox | Box Cox Transformation

## -- C --

coef.mdl_df | Extract model coefficients from a mable
coef.mdl_lst | Extract model coefficients from a mable
coef.mdl_ts | Extract model coefficients from a mable
coherent_cmat | Zero-constraint matrix for coherent time series
coherent_smat | Structural (summing) matrix for coherent time series
combination_ensemble | Ensemble combination
combination_model | Combination modelling
combination_weighted | Weighted combination
common_periods | Extract frequencies for common seasonal periods
common_periods.default | Extract frequencies for common seasonal periods
common_periods.interval | Extract frequencies for common seasonal periods
common_periods.tbl_ts | Extract frequencies for common seasonal periods
common_xregs | Common exogenous regressors
components.mdl_df | Extract components from a fitted model
components.mdl_ts | Extract components from a fitted model
CRPS | Distribution accuracy measures

## -- D --

dable | Create a dable object
decomposition_model | Decomposition modelling
directional_accuracy_measures | Directional accuracy measures
distribution_accuracy_measures | Distribution accuracy measures
distribution_var | Return distribution variable

## -- E --

estimate | Estimate a model
estimate.tbl_ts | Estimate a model

## -- F --

fable | Create a fable object
fabletools | fabletools: Core Tools for Packages in the 'fable' Framework
features | Extract features from a dataset
features_all | Extract features from a dataset
features_at | Extract features from a dataset
features_if | Extract features from a dataset
feature_set | Create a feature set from tags
fitted.mdl_df | Extract fitted values from models
fitted.mdl_ts | Extract fitted values from models
forecast.mdl_df | Produce forecasts
forecast.mdl_ts | Produce forecasts
fourier | Common exogenous regressors

## -- G --

generate.mdl_df | Generate responses from a mable
generate.mdl_ts | Generate responses from a mable
get_frequencies | Extract frequencies for common seasonal periods
get_frequencies.character | Extract frequencies for common seasonal periods
get_frequencies.NULL | Extract frequencies for common seasonal periods
get_frequencies.numeric | Extract frequencies for common seasonal periods
get_frequencies.Period | Extract frequencies for common seasonal periods
glance.mdl_df | Glance a mable
glance.mdl_lst | Glance a mable
glance.mdl_ts | Glance a mable

## -- H --

hfitted | Extract fitted values from models
hypothesize.mdl_df | Run a hypothesis test from a mable
hypothesize.mdl_ts | Run a hypothesis test from a mable

## -- I --

interpolate.mdl_df | Interpolate missing values
interpolate.mdl_ts | Interpolate missing values
interval_accuracy_measures | Interval estimate accuracy measures
invert_transformation | Create a new modelling transformation
inv_box_cox | Box Cox Transformation
IRF | Compute Impulse Response Function (IRF)
is_aggregated | Is the element an aggregation of smaller data
is_dable | Is the object a dable
is_fable | Is the object a fable
is_mable | Is the object a mable
is_model | Is the object a model

## -- M --

MAAPE | Mean Arctangent Absolute Percentage Error
mable | Create a new mable
mable_vars | Return model column variables
MAE | Point estimate accuracy measures
MAPE | Point estimate accuracy measures
MASE | Point estimate accuracy measures
MDA | Directional accuracy measures
MDPV | Directional accuracy measures
MDV | Directional accuracy measures
ME | Point estimate accuracy measures
middle_out | Middle out forecast reconciliation
min_trace | Minimum trace forecast reconciliation
model | Estimate models
model.tbl_ts | Estimate models
model_lhs | Extract the left hand side of a model
model_rhs | Extract the right hand side of a model
model_sum | Provide a succinct summary of a model
MPE | Point estimate accuracy measures
MSE | Point estimate accuracy measures

## -- N --

new_model_class | Create a new class of models
new_model_definition | Create a new class of models
new_specials | Create evaluation environment for specials
new_transformation | Create a new modelling transformation

## -- O --

outliers | Identify outliers
outliers.mdl_df | Identify outliers
outliers.mdl_ts | Identify outliers

## -- P --

percentile_score | Distribution accuracy measures
pinball_loss | Interval estimate accuracy measures
point_accuracy_measures | Point estimate accuracy measures

## -- Q --

quantile_score | Distribution accuracy measures

## -- R --

reconcile | Forecast reconciliation
reconcile.mdl_df | Forecast reconciliation
refit.mdl_df | Refit a mable to a new dataset
refit.mdl_ts | Refit a mable to a new dataset
register_feature | Register a feature function
report | Report information about an object
residuals.mdl_df | Extract residuals values from models
residuals.mdl_ts | Extract residuals values from models
response | Extract the response variable from a model
response_vars | Return response variables
RMSE | Point estimate accuracy measures
RMSSE | Point estimate accuracy measures

## -- S --

scaled_pinball_loss | Interval estimate accuracy measures
scenarios | A set of future scenarios for forecasting
season | Common exogenous regressors
skill_score | Forecast skill score measure
special_xreg | Helper special for producing a model matrix of exogenous regressors
stream | Extend a fitted model with new data
stream.mdl_df | Extend a fitted model with new data

## -- T --

tidy.mdl_df | Extract model coefficients from a mable
tidy.mdl_lst | Extract model coefficients from a mable
tidy.mdl_ts | Extract model coefficients from a mable
top_down | Top down forecast reconciliation
trend | Common exogenous regressors

## -- W --

winkler_score | Interval estimate accuracy measures