nixtla_client_historic {nixtlar} | R Documentation |
Generate 'TimeGPT' forecast for the in-sample period (historical period).
Description
Generate 'TimeGPT' forecast for the in-sample period (historical period).
Usage
nixtla_client_historic(
df,
freq = NULL,
id_col = NULL,
time_col = "ds",
target_col = "y",
level = NULL,
finetune_steps = 0,
finetune_loss = "default",
clean_ex_first = TRUE
)
Arguments
df |
A tsibble or a data frame with time series data. |
freq |
Frequency of the data. |
id_col |
Column that identifies each series. |
time_col |
Column that identifies each timestep. |
target_col |
Column that contains the target variable. |
level |
The confidence levels (0-100) for the prediction intervals. |
finetune_steps |
Number of steps used to finetune 'TimeGPT' in the new data. |
finetune_loss |
Loss function to use for finetuning. Options are: "default", "mae", "mse", "rmse", "mape", and "smape". |
clean_ex_first |
Clean exogenous signal before making the forecasts using 'TimeGPT'. |
Value
'TimeGPT”s forecast for the in-sample period.
Examples
## Not run:
nixtlar::nixtla_set_api_key("YOUR_API_KEY")
df <- nixtlar::electricity
fcst <- nixtlar::nixtla_client_historic(df, id_col="unique_id", level=c(80,95))
## End(Not run)
[Package nixtlar version 0.5.2 Index]