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fabletools

The R package fabletools provides tools for building modelling packages, with a focus on time series forecasting. This package allows package developers to extend fable with additional models, without needing to depend on the models supported by fable.

Installation

You could install the stable version on CRAN:

install.packages("fabletools")

You can install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("tidyverts/fabletools")

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Version

Install

install.packages('fabletools')

Monthly Downloads

15,111

Version

0.6.1

License

GPL-3

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/tidyverts/fabletools

Homepage

https://fabletools.tidyverts.org/

Maintainer

Mitchell O'Hara-Wild

Last Published

February 16th, 2026

Functions in fabletools (0.6.1)

combination_model

Combination modelling

combination_weighted

Weighted combination

distribution_var

Return distribution variable

features_by_tag

Features by tag

Create a fable object

Internal vctrs methods

autoplot.tbl_ts

Plot time series from a tsibble

autoplot.fbl_ts

Plot a set of forecasts

Directional accuracy measures

percentile_score

Distribution accuracy measures

Provide a succinct summary of a model

Extract fitted values from models

new_model_class

Create a new class of models

generate.mdl_df

Generate responses from a mable

forecast.mdl_df

Produce forecasts

combination_ensemble

Ensemble combination

Box Cox Transformation

Estimate a model

Create a dable object

decomposition_model

Decomposition modelling

Is the object a model

Is the object a mable

Extract features from a dataset

Extract frequencies for common seasonal periods

Interval estimate accuracy measures

hypothesize.mdl_df

Run a hypothesis test from a mable

Forecast reconciliation

Internal vctrs methods

Construct a new set of forecasts

features_by_pkg

Features by package

interpolate.mdl_df

Interpolate missing values

Helper special for producing a model matrix of exogenous regressors

Extract the left hand side of a model

parse_model_rhs

Parse the RHS of the model formula for specials

Extend a fitted model with new data

Extract the right hand side of a model

Point estimate accuracy measures

Create a feature set from tags

Is the object a dable

fabletools-package

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

Objects exported from other packages

A set of future scenarios for forecasting

Is the element an aggregation of smaller data

parse_model_lhs

Parse the RHS of the model formula for transformations

Parse the model specification for specials

Extract the response variable from a model

Internal vctrs methods

Is the object a fable

Return model column variables

Recursively traverse an object

Return response variables

Create a new mable

Identify outliers

Unpack a hilo column

validate_formula

Validate the user provided model

Refit a mable to a new dataset

Middle out forecast reconciliation

Forecast skill score measure

register_feature

Register a feature function

Minimum trace forecast reconciliation

Estimate models

new_transformation

Create a new modelling transformation

Create evaluation environment for specials

Report information about an object

residuals.mdl_df

Extract residuals values from models

Extract model coefficients from a mable

Top down forecast reconciliation

Coerce to a fable object

aggregation-vctrs

Internal vctrs methods

Compute Impulse Response Function (IRF)

aggregate_index

Expand a dataset to include temporal aggregates

accuracy.mdl_df

Evaluate accuracy of a forecast or model

Create an aggregation vector

Expand a dataset to include other levels of aggregation

Coerce to a dable object

Mean Arctangent Absolute Percentage Error

Coerce a dataset to a mable

Augment a mable

Bottom up forecast reconciliation

autoplot.dcmp_ts

Decomposition plots

components.mdl_df

Extract components from a fitted model

Bias adjust back-transformation functions

Common exogenous regressors