accuracy | Evaluate accuracy of a forecast or model |
aggregate_index | Expand a dataset to include temporal aggregates |
aggregate_key | Expand a dataset to include other levels of aggregation |
aggregation-vctrs | Internal vctrs methods |
agg_vec | Create an aggregation vector |
as-dable | Coerce to a dable object |
as-fable | Coerce to a fable object |
as_mable | Coerce a dataset to a mable |
augment | Augment a mable |
autoplot.dcmp_ts | Decomposition plots |
autoplot.fbl_ts | Plot a set of forecasts |
autoplot.tbl_ts | Plot time series from a tsibble |
bias_adjust | Bias adjust back-transformation functions |
bottom_up | Bottom up forecast reconciliation |
box_cox | Box Cox Transformation |
combination_ensemble | Ensemble combination |
combination_model | Combination modelling |
combination_weighted | Weighted combination |
common_xregs | Common exogenous regressors |
components | Extract components from a fitted model |
construct_fc | Construct a new set of forecasts |
dable | Create a dable object |
dable-vctrs | Internal vctrs methods |
decomposition_model | Decomposition modelling |
directional_accuracy_measures | Directional accuracy measures |
distribution_accuracy_measures | Distribution accuracy measures |
distribution_var | Return distribution variable |
estimate | Estimate a model |
fable | Create a fable object |
fabletools-package | fabletools: Core Tools for Packages in the 'fable' Framework |
fable-vctrs | Internal vctrs methods |
features | Extract features from a dataset |
features_by_pkg | Features by package |
features_by_tag | Features by tag |
feature_set | Create a feature set from tags |
fitted.mdl_df | Extract fitted values from models |
forecast | Produce forecasts |
freq_tools | Extract frequencies for common seasonal periods |
generate.mdl_df | Generate responses from a mable |
glance | Glance a mable |
hypothesize.mdl_df | Run a hypothesis test from a mable |
interpolate | Interpolate missing values |
interval_accuracy_measures | Interval estimate accuracy measures |
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 |
MAAPE | Mean Arctangent Absolute Percentage Error |
mable | Create a new mable |
mable_vars | Return model column variables |
mable-vctrs | Internal vctrs methods |
middle_out | Middle out forecast reconciliation |
min_trace | Minimum trace forecast reconciliation |
model | 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 |
new-model-class | Create a new class of models |
new_specials | Create evaluation environment for specials |
new_transformation | Create a new modelling transformation |
null_model | NULL model |
outliers | Identify outliers |
parse_model | Parse the model specification for specials |
parse_model_lhs | Parse the RHS of the model formula for transformations |
parse_model_rhs | Parse the RHS of the model formula for specials |
point_accuracy_measures | Point estimate accuracy measures |
reconcile | Forecast reconciliation |
reexports | Objects exported from other packages |
refit | 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 |
response | Extract the response variable from a model |
response_vars | Return response variables |
scenarios | A set of future scenarios for forecasting |
skill_score | Forecast skill score measure |
special_xreg | Helper special for producing a model matrix of exogenous... |
stream | Extend a fitted model with new data |
tidy | Extract model coefficients from a mable |
top_down | Top down forecast reconciliation |
traverse | Recursively traverse an object |
unpack_hilo | Unpack a hilo column |
validate_formula | Validate the user provided model |
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