---
title: regr
description: 'The page covers two main aspects of the OpenBB finance platform: Regression
  Forecasting and Displaying Regression Forecasting. It provides source codes, defines
  parameters and returns related to the regression model and data. Users can find
  additional features like forecasting horizon, historical forecasting, and prediction
  capabilities. The option of view-chart allows users to visualise the data forecast.'
keywords:
- Regression Forecasting
- Source code
- OpenBB finance
- parameters
- returns
- charts
- perform analysis
- forecast horizon
- historical forecasting
- data series
- Regression Model
- mean average precision error
- RNN model
- Predictions
- Adjusted Data
---

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

<HeadTitle title="forecast.regr - Reference | OpenBB SDK Docs" />

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

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<TabItem value="model" label="Model" default>

Perform Regression Forecasting

Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/forecast/regr_model.py#L22)]

```python
openbb.forecast.regr(data: Union[pd.Series, pd.DataFrame], target_column: str = "close", n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, output_chunk_length: int = 1, lags: Union[int, List[int]] = 72)
```

---

## Parameters

| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| data | Union[pd.Series, pd.DataFrame] | Input Data | None | False |
| n_predict | int | Days to predict. Defaults to 5. | 5 | True |
| target_column | str | Target column to forecast. Defaults to "close". | close | True |
| train_split | float | Train/val split. Defaults to 0.85. | 0.85 | True |
| past_covariates | str | Multiple secondary columns to factor in when forecasting. Defaults to None. | None | True |
| forecast_horizon | int | Forecast horizon when performing historical forecasting. Defaults to 5. | 5 | True |
| output_chunk_length | int | The length of the forecast of the model. Defaults to 1. | 1 | True |
| lags | Union[int, List[int]] | lagged target values to predict the next time step | 72 | True |


---

## Returns

| Type | Description |
| ---- | ----------- |
| Tuple[List[TimeSeries], List[TimeSeries], List[TimeSeries], float, type[RegressionModel]] | Adjusted Data series,<br/>Historical forecast by best RNN model,<br/>list of Predictions,<br/>Mean average precision error,<br/>Best Regression Model. |
---

</TabItem>
<TabItem value="view" label="Chart">

Display Regression Forecasting

Source Code: [[link](https://github.com/OpenBB-finance/OpenBBTerminal/tree/main/openbb_terminal/forecast/regr_view.py#L20)]

```python
openbb.forecast.regr_chart(data: Union[pd.Series, pd.DataFrame], target_column: str = "close", dataset_name: str = "", n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, output_chunk_length: int = 1, lags: Union[int, List[int]] = 72, export: str = "", residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, explainability_raw: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None)
```

---

## Parameters

| Name | Type | Description | Default | Optional |
| ---- | ---- | ----------- | ------- | -------- |
| data | Union[pd.Series, pd.DataFrame] | Input Data | None | False |
| target_column | str | Target column to forecast. Defaults to "close". | close | True |
| dataset_name | str | The name of the ticker to be predicted |  | True |
| n_predict | int | Days to predict. Defaults to 5. | 5 | True |
| train_split | float | Train/val split. Defaults to 0.85. | 0.85 | True |
| past_covariates | str | Multiple secondary columns to factor in when forecasting. Defaults to None. | None | True |
| forecast_horizon | int | Forecast horizon when performing historical forecasting. Defaults to 5. | 5 | True |
| output_chunk_length | int | The length of the forecast of the model. Defaults to 1. | 1 | True |
| lags | Union[int, List[int]] | lagged target values to predict the next time step | 72 | True |
| export | str | Format to export data |  | True |
| residuals | bool | Whether to show residuals for the model. Defaults to False. | False | True |
| forecast_only | bool | Whether to only show dates in the forecasting range. Defaults to False. | False | True |
| start_date | Optional[datetime] | The starting date to perform analysis, data before this is trimmed. Defaults to None. | None | True |
| end_date | Optional[datetime] | The ending date to perform analysis, data after this is trimmed. Defaults to None. | None | True |
| naive | bool | Whether to show the naive baseline. This just assumes the closing price will be the same<br/>as the previous day's closing price. Defaults to False. | False | True |
| external_axes | Optional[List[plt.axes]] | External axes to plot on | None | True |


---

## Returns

This function does not return anything

---

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