recommend_model: Rank registered models for a series

In forecastsuite: Multi-Model Time Series Forecasting Toolkit and Local App

Rank registered models for a series

Description

Scores every candidate model against analyze_series()'s measured trend/seasonality/regularity, with short human-readable reasons – no model is actually fit, so this is fast enough to run right after a dataset is finalized.

Usage

recommend_model(analysis, holidays_configured = FALSE, candidates = NULL)

Arguments

analysis	The list returned by analyze_series().
holidays_configured	Logical; whether holidays are configured for this dataset. Every model except Prophet is scored down when TRUE, since none of the others model holiday effects.
candidates	Character vector of registry keys to score (see list_models()), or NULL (the default) to score every currently available registered model.

Value

A data frame with columns model (label), key, score, and reason, sorted by score descending.

Examples

df <- tibble::tibble(ds = as.Date("2024-01-01") + 0:59, y = 1:60 + rnorm(60))
recommend_model(analyze_series(df, "day"))

forecastsuite documentation built on Oct. 18, 2026, 5:08 p.m.