This package is considered a duplicate. The official version of this package is found at:https://tidyverts.r-universe.dev/fabletools

Package: fabletools 0.8.0.9000

Mitchell OHara-Wild

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

Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.

Authors:Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Di Cook [ctb], George Athanasopoulos [ctb], David Holt [ctb]

fabletools_0.8.0.9000.tar.gz
fabletools_0.8.0.9000.zip(r-4.7)fabletools_0.8.0.9000.zip(r-4.6)fabletools_0.8.0.9000.zip(r-4.5)
fabletools_0.8.0.9000.tgz(r-4.6-any)fabletools_0.8.0.9000.tgz(r-4.5-any)
fabletools_0.8.0.9000.tar.gz(r-4.7-any)fabletools_0.8.0.9000.tar.gz(r-4.6-any)
fabletools_0.8.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fabletools/json (API)

# Install 'fabletools' in R:

install.packages('fabletools', repos = c('https://robjhyndman.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tidyverts/fabletools/issues

Pkgdown/docs site:https://fabletools.tidyverts.org

On CRAN:

12.41 score 96 stars 24 packages 581 scripts 11k downloads 102 exports 41 dependencies

Last updated from:2a4db8090c. Checks:9 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	229
source / vignettes	OK	339
linux-release-x86_64	OK	213
macos-release-arm64	OK	149
macos-oldrel-arm64	OK	158
windows-devel	OK	172
windows-release	OK	191
windows-oldrel	OK	169
wasm-release	OK	169

Exports:%>%accuracy ACF1 agg_vec aggregate_key as_dable as_fable as_mable as_tsibble augment autolayer autoplot bias_adjust bottom_up box_cox coherent_cmat coherent_smat combination_ensemble combination_model combination_weighted common_periods common_xregs components construct_fc CRPS dable decomposition_model directional_accuracy_measures distribution_accuracy_measures distribution_var equation estimate fable feature_set features features_all features_at features_if forecast generate get_frequencies glance hfitted hilo hypothesize interpolate interval_accuracy_measures inv_box_cox invert_transformation IRF is_aggregated is_dable is_fable is_mable is_model is_null_model MAAPE mable mable_vars MAE MAPE MASE MDA MDPV MDV ME middle_out min_trace model model_lhs model_rhs model_sum MPE MSE new_model_class new_model_definition new_specials new_transformation null_model outliers percentile_score pinball_loss point_accuracy_measures quantile_score reconcile refit register_feature report response response_vars RMSE RMSSE scaled_pinball_loss scenarios skill_score special_xreg stream tidy top_down unpack_hilo vars winkler_score

Dependencies:anytime BH cli cpp11 digest distributional dplyr farver generics ggdist ggplot2 glue gtable isoband labeling lifecycle lubridate magrittr numDeriv pillar pkgconfig progressr purrr quadprog R6 RColorBrewer Rcpp rlang S7 scales stringi stringr tibble tidyr tidyselect timechange tsibble utf8 vctrs viridisLite withr

Extending fabletools: Models

Rendered fromextension_models.Rmdusingknitr::rmarkdown

Last update: 2020-08-04
Started: 2020-03-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
fabletools: Core Tools for Packages in the 'fable' Framework	fabletools-package fabletools
Evaluate accuracy of a forecast or model	accuracy.fbl_ts accuracy.mdl_df accuracy.mdl_lst accuracy.mdl_ts
Create an aggregation vector	agg_vec
Expand a dataset to include temporal aggregates	aggregate_index
Expand a dataset to include other levels of aggregation	aggregate_key
Coerce to a dable object	as_dable as_dable.tbl_df as_dable.tbl_ts
Coerce to a fable object	as_fable as_fable.fbl_ts as_fable.forecast as_fable.grouped_df as_fable.grouped_ts as_fable.tbl_df as_fable.tbl_ts
Coerce a dataset to a mable	as_mable as_mable.data.frame
Augment a mable	augment.mdl_df augment.mdl_lst augment.mdl_ts
Decomposition plots	autoplot.dcmp_ts
Plot a set of forecasts	autolayer.fbl_ts autoplot.fbl_ts
Plot time series from a tsibble	autolayer.tbl_ts autoplot.tbl_ts
Bottom up forecast reconciliation	bottom_up
Box Cox Transformation	box_cox inv_box_cox
Zero-constraint matrix for coherent time series	coherent_cmat
Structural (summing) matrix for coherent time series	coherent_smat coherent_smat.tbl
Ensemble combination	combination_ensemble
Combination modelling	combination_model
Weighted combination	combination_weighted
Extract frequencies for common seasonal periods	common_periods common_periods.default common_periods.interval common_periods.tbl_ts get_frequencies get_frequencies.character get_frequencies.NULL get_frequencies.numeric get_frequencies.Period
Common exogenous regressors	common_xregs fourier season trend
Extract components from a fitted model	components.mdl_df components.mdl_ts
Create a dable object	dable
Decomposition modelling	decomposition_model
Return distribution variable	distribution_var
Estimate a model	estimate estimate.tbl_ts
Create a fable object	fable
Create a feature set from tags	feature_set
Extract features from a dataset	features features_all features_at features_if
Extract fitted values from models	fitted.mdl_df fitted.mdl_ts hfitted
Produce forecasts	forecast.mdl_df forecast.mdl_ts
Generate responses from a mable	generate.mdl_df generate.mdl_ts
Glance a mable	glance.mdl_df glance.mdl_lst glance.mdl_ts
Run a hypothesis test from a mable	hypothesize.mdl_df hypothesize.mdl_ts
Interpolate missing values	interpolate.mdl_df interpolate.mdl_ts
Compute Impulse Response Function (IRF)	IRF
Is the element an aggregation of smaller data	is_aggregated
Is the object a dable	is_dable
Is the object a fable	is_fable
Is the object a mable	is_mable
Is the object a model	is_model
Mean Arctangent Absolute Percentage Error	MAAPE
Create a new mable	mable
Return model column variables	mable_vars
Directional accuracy measures	directional_accuracy_measures MDA MDPV MDV
Point estimate accuracy measures	ACF1 MAE MAPE MASE ME MPE MSE point_accuracy_measures RMSE RMSSE
Middle out forecast reconciliation	middle_out
Minimum trace forecast reconciliation	min_trace
Estimate models	model model.tbl_ts
Extract the left hand side of a model	model_lhs
Extract the right hand side of a model	model_rhs
Provide a succinct summary of a model	model_sum
Create a new class of models	new_model_class new_model_definition
Create evaluation environment for specials	new_specials
Create a new modelling transformation	invert_transformation new_transformation
Identify outliers	outliers outliers.mdl_df outliers.mdl_ts
Distribution accuracy measures	CRPS distribution_accuracy_measures percentile_score quantile_score
Forecast reconciliation	reconcile reconcile.mdl_df
Refit a mable to a new dataset	refit.mdl_df refit.mdl_ts
Register a feature function	register_feature
Report information about an object	report
Extract residuals values from models	residuals.mdl_df residuals.mdl_ts
Extract the response variable from a model	response
Return response variables	response_vars
A set of future scenarios for forecasting	scenarios
Forecast skill score measure	skill_score
Helper special for producing a model matrix of exogenous regressors	special_xreg
Extend a fitted model with new data	stream stream.mdl_df
Extract model coefficients from a mable	coef.mdl_df coef.mdl_lst coef.mdl_ts tidy.mdl_df tidy.mdl_lst tidy.mdl_ts
Top down forecast reconciliation	top_down
Interval estimate accuracy measures	interval_accuracy_measures pinball_loss scaled_pinball_loss winkler_score