Extract Residuals Information

This is a convenience function to unnest model residuals

Usage

modeltime_residuals(object, new_data = NULL, quiet = TRUE, ...)

Arguments

object

A Modeltime Table

new_data

A tibble to predict and calculate residuals on. If provided, overrides any calibration data.

quiet

Hide errors (TRUE, the default), or display them as they occur?

...

Not currently used.

Value

A tibble with residuals.

Examples

library(dplyr)
library(lubridate)
library(timetk)
library(parsnip)
library(rsample)

# Data
m750 <- m4_monthly %>% filter(id == "M750")

# Split Data 80/20
splits <- initial_time_split(m750, prop = 0.9)

# --- MODELS ---

# Model 1: prophet ----
model_fit_prophet <- prophet_reg() %>%
    set_engine(engine = "prophet") %>%
    fit(value ~ date, data = training(splits))
#> Disabling weekly seasonality. Run prophet with weekly.seasonality=TRUE to override this.
#> Disabling daily seasonality. Run prophet with daily.seasonality=TRUE to override this.


# ---- MODELTIME TABLE ----

models_tbl <- modeltime_table(
    model_fit_prophet
)

# ---- RESIDUALS ----

# In-Sample
models_tbl %>%
    modeltime_calibrate(new_data = training(splits)) %>%
    modeltime_residuals() %>%
    plot_modeltime_residuals(.interactive = FALSE)


# Out-of-Sample
models_tbl %>%
    modeltime_calibrate(new_data = testing(splits)) %>%
    modeltime_residuals() %>%
    plot_modeltime_residuals(.interactive = FALSE)