View source: R/boilerplate-lm.R
| ts_auto_lm | R Documentation | 
This is a boilerplate function to create automatically the following:
recipe
model specification
workflow
calibration tibble and plot
ts_auto_lm(
  .data,
  .date_col,
  .value_col,
  .formula,
  .rsamp_obj,
  .prefix = "ts_lm",
  .bootstrap_final = FALSE
)
| .data | The data being passed to the function. The time-series object. | 
| .date_col | The column that holds the datetime. | 
| .value_col | The column that has the value | 
| .formula | The formula that is passed to the recipe like  | 
| .rsamp_obj | The rsample splits object | 
| .prefix | Default is  | 
| .bootstrap_final | Not yet implemented. | 
This uses parsnip::linear_reg() and sets the engine to lm
A list
Steven P. Sanderson II, MPH
https://parsnip.tidymodels.org/reference/linear_reg.html
Other Boiler_Plate: 
ts_auto_arima(),
ts_auto_arima_xgboost(),
ts_auto_croston(),
ts_auto_exp_smoothing(),
ts_auto_glmnet(),
ts_auto_mars(),
ts_auto_nnetar(),
ts_auto_prophet_boost(),
ts_auto_prophet_reg(),
ts_auto_smooth_es(),
ts_auto_svm_poly(),
ts_auto_svm_rbf(),
ts_auto_theta(),
ts_auto_xgboost()
library(dplyr)
library(timetk)
library(modeltime)
data <- AirPassengers %>%
  ts_to_tbl() %>%
  select(-index)
splits <- time_series_split(
  data
  , date_col
  , assess = 12
  , skip = 3
  , cumulative = TRUE
)
ts_lm <- ts_auto_lm(
  .data = data,
  .date_col = date_col,
  .value_col = value,
  .rsamp_obj = splits,
  .formula = value ~ .,
)
ts_lm$recipe_info
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