# {py:mod}`causalis.scenarios.unconfoundedness.dgp`

```{py:module} causalis.scenarios.unconfoundedness.dgp
```

```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp
:allowtitles:
```

## Module Contents

### Functions

````{list-table}
:class: autosummary longtable
:align: left

* - {py:obj}`obs_linear_26_dataset <causalis.scenarios.unconfoundedness.dgp.obs_linear_26_dataset>`
  - ```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.obs_linear_26_dataset
    :summary:
    ```
* - {py:obj}`generate_obs_hte_26 <causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26>`
  - ```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26
    :summary:
    ```
* - {py:obj}`generate_obs_hte_26_rich <causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26_rich>`
  - ```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26_rich
    :summary:
    ```
* - {py:obj}`generate_obs_hte_binary_26 <causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_binary_26>`
  - ```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_binary_26
    :summary:
    ```
````

### API

````{py:function} obs_linear_26_dataset(n: int = 10000, seed: int = 42, include_oracle: bool = True, return_causal_data: bool = True)
:canonical: causalis.scenarios.unconfoundedness.dgp.obs_linear_26_dataset

```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.obs_linear_26_dataset
```
````

````{py:function} generate_obs_hte_26(n: int = 10000, seed: int = 42, include_oracle: bool = True, return_causal_data: bool = True) -> typing.Union[pandas.DataFrame, causalis.dgp.causaldata.CausalData]
:canonical: causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26

```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26
```
````

````{py:function} generate_obs_hte_26_rich(n: int = 100000, seed: int = 42, include_oracle: bool = True, return_causal_data: bool = True) -> typing.Union[pandas.DataFrame, causalis.dgp.causaldata.CausalData]
:canonical: causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26_rich

```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_26_rich
```
````

````{py:function} generate_obs_hte_binary_26(n: int = 100000, seed: int = 42, include_oracle: bool = True, return_causal_data: bool = True) -> typing.Union[pandas.DataFrame, causalis.dgp.causaldata.CausalData]
:canonical: causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_binary_26

```{autodoc2-docstring} causalis.scenarios.unconfoundedness.dgp.generate_obs_hte_binary_26
```
````
