# The Tidymodels Extension for Time Series Modeling

## Documentation for package ‘modeltime’ version 1.2.8

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

## Help Pages

A B C D E G I J L M N O P R S T U W

## -- A --

adam_params | Tuning Parameters for ADAM Models
adam_reg | General Interface for ADAM Regression Models
add_modeltime_model | Add a Model into a Modeltime Table
arima_boost | General Interface for "Boosted" ARIMA Regression Models
arima_params | Tuning Parameters for ARIMA Models
arima_reg | General Interface for ARIMA Regression Models
as_modeltime_table | Scale forecast analysis with a Modeltime Table

## -- B --

bake_xreg_recipe | Developer Tools for processing XREGS (Regressors)

## -- C --

changepoint_num | Tuning Parameters for Prophet Models
changepoint_range | Tuning Parameters for Prophet Models
combination_method | Tuning Parameters for TEMPORAL HIERARCHICAL Models
combine_modeltime_tables | Combine multiple Modeltime Tables into a single Modeltime Table
control_fit_workflowset | Control aspects of the training process
control_modeltime | Control aspects of the training process
control_nested_fit | Control aspects of the training process
control_nested_forecast | Control aspects of the training process
control_nested_refit | Control aspects of the training process
control_refit | Control aspects of the training process
create_model_grid | Helper to make 'parsnip' model specs from a 'dials' parameter grid
create_xreg_recipe | Developer Tools for preparing XREGS (Regressors)

## -- D --

damping | Tuning Parameters for Exponential Smoothing Models
damping_smooth | Tuning Parameters for Exponential Smoothing Models
default_forecast_accuracy_metric_set | Forecast Accuracy Metrics Sets
distribution | Tuning Parameters for ADAM Models
drop_modeltime_model | Drop a Model from a Modeltime Table

## -- E --

error | Tuning Parameters for Exponential Smoothing Models
exp_smoothing | General Interface for Exponential Smoothing State Space Models
exp_smoothing_params | Tuning Parameters for Exponential Smoothing Models
extended_forecast_accuracy_metric_set | Forecast Accuracy Metrics Sets
extend_timeseries | Prepared Nested Modeltime Data
extract_nested_best_model_report | Log Extractor Functions for Modeltime Nested Tables
extract_nested_error_report | Log Extractor Functions for Modeltime Nested Tables
extract_nested_future_forecast | Log Extractor Functions for Modeltime Nested Tables
extract_nested_modeltime_table | Log Extractor Functions for Modeltime Nested Tables
extract_nested_test_accuracy | Log Extractor Functions for Modeltime Nested Tables
extract_nested_test_forecast | Log Extractor Functions for Modeltime Nested Tables
extract_nested_test_split | Log Extractor Functions for Modeltime Nested Tables
extract_nested_train_split | Log Extractor Functions for Modeltime Nested Tables

## -- G --

get_arima_description | Get model descriptions for Arima objects
get_model_description | Get model descriptions for parsnip, workflows & modeltime objects
get_tbats_description | Get model descriptions for TBATS objects
growth | Tuning Parameters for Prophet Models

## -- I --

information_criteria | Tuning Parameters for ADAM Models

## -- J --

juice_xreg_recipe | Developer Tools for processing XREGS (Regressors)

## -- L --

log_extractors | Log Extractor Functions for Modeltime Nested Tables

## -- M --

m750 | The 750th Monthly Time Series used in the M4 Competition
m750_models | Three (3) Models trained on the M750 Data (Training Set)
m750_splits | The results of train/test splitting the M750 Data
m750_training_resamples | The Time Series Cross Validation Resamples the M750 Data (Training Set)
maape | Mean Arctangent Absolute Percentage Error
maape_vec | Mean Arctangent Absolute Percentage Error
metric_sets | Forecast Accuracy Metrics Sets
modeltime_accuracy | Calculate Accuracy Metrics
modeltime_calibrate | Preparation for forecasting
modeltime_fit_workflowset | Fit a 'workflowset' object to one or multiple time series
modeltime_forecast | Forecast future data
modeltime_nested_fit | Fit Tidymodels Workflows to Nested Time Series
modeltime_nested_forecast | Modeltime Nested Forecast
modeltime_nested_refit | Refits a Nested Modeltime Table
modeltime_nested_select_best | Select the Best Models from Nested Modeltime Table
modeltime_refit | Refit one or more trained models to new data
modeltime_residuals | Extract Residuals Information
modeltime_residuals_test | Apply Statistical Tests to Residuals
modeltime_table | Scale forecast analysis with a Modeltime Table

## -- N --

naive_reg | General Interface for NAIVE Forecast Models
nest_timeseries | Prepared Nested Modeltime Data
new_modeltime_bridge | Constructor for creating modeltime models
nnetar_params | Tuning Parameters for NNETAR Models
nnetar_reg | General Interface for NNETAR Regression Models
non_seasonal_ar | Tuning Parameters for ARIMA Models
non_seasonal_differences | Tuning Parameters for ARIMA Models
non_seasonal_ma | Tuning Parameters for ARIMA Models
num_networks | Tuning Parameters for NNETAR Models

## -- O --

outliers_treatment | Tuning Parameters for ADAM Models

## -- P --

panel_tail | Filter the last N rows (Tail) for multiple time series
parallel_start | Start parallel clusters using 'parallel' package
parallel_stop | Start parallel clusters using 'parallel' package
parse_index | Developer Tools for parsing date and date-time information
parse_index_from_data | Developer Tools for parsing date and date-time information
parse_period_from_index | Developer Tools for parsing date and date-time information
plot_modeltime_forecast | Interactive Forecast Visualization
plot_modeltime_residuals | Interactive Residuals Visualization
pluck_modeltime_model | Extract model by model id in a Modeltime Table
pluck_modeltime_model.mdl_time_tbl | Extract model by model id in a Modeltime Table
prep_nested | Prepared Nested Modeltime Data
prior_scale_changepoints | Tuning Parameters for Prophet Models
prior_scale_holidays | Tuning Parameters for Prophet Models
prior_scale_seasonality | Tuning Parameters for Prophet Models
probability_model | Tuning Parameters for ADAM Models
prophet_boost | General Interface for Boosted PROPHET Time Series Models
prophet_params | Tuning Parameters for Prophet Models
prophet_reg | General Interface for PROPHET Time Series Models
pull_modeltime_model | Extract model by model id in a Modeltime Table
pull_modeltime_residuals | Extracts modeltime residuals data from a Modeltime Model
pull_parsnip_preprocessor | Pulls the Formula from a Fitted Parsnip Model Object

## -- R --

recipe_helpers | Developer Tools for processing XREGS (Regressors)
recursive | Create a Recursive Time Series Model from a Parsnip or Workflow Regression Model
regressors_treatment | Tuning Parameters for ADAM Models

## -- S --

season | Tuning Parameters for Exponential Smoothing Models
seasonality_daily | Tuning Parameters for Prophet Models
seasonality_weekly | Tuning Parameters for Prophet Models
seasonality_yearly | Tuning Parameters for Prophet Models
seasonal_ar | Tuning Parameters for ARIMA Models
seasonal_differences | Tuning Parameters for ARIMA Models
seasonal_ma | Tuning Parameters for ARIMA Models
seasonal_period | Tuning Parameters for Time Series (ts-class) Models
seasonal_reg | General Interface for Multiple Seasonality Regression Models (TBATS, STLM)
select_order | Tuning Parameters for ADAM Models
smooth_level | Tuning Parameters for Exponential Smoothing Models
smooth_seasonal | Tuning Parameters for Exponential Smoothing Models
smooth_trend | Tuning Parameters for Exponential Smoothing Models
split_nested_timeseries | Prepared Nested Modeltime Data
summarize_accuracy_metrics | Summarize Accuracy Metrics

## -- T --

table_modeltime_accuracy | Interactive Accuracy Tables
temporal_hierarchy | General Interface for Temporal Hierarchical Forecasting (THIEF) Models
temporal_hierarchy_params | Tuning Parameters for TEMPORAL HIERARCHICAL Models
time_series_params | Tuning Parameters for Time Series (ts-class) Models
trend | Tuning Parameters for Exponential Smoothing Models
trend_smooth | Tuning Parameters for Exponential Smoothing Models

## -- U --

update_modeltime_description | Update the model description by model id in a Modeltime Table
update_modeltime_model | Update the model by model id in a Modeltime Table
update_model_description | Update the model description by model id in a Modeltime Table
use_constant | Tuning Parameters for ADAM Models
use_model | Tuning Parameters for TEMPORAL HIERARCHICAL Models

## -- W --

window_reg | General Interface for Window Forecast Models