# Generalized score with marginal likelihood

## Generalized score with marginal likelihood for single dimensional variables

Calculate the local score by negative marginal likelihood, based on a regression model in RKHS [1].

### Usage

```
from causallearn.score.LocalScoreFunction import local_score_marginal_general
score = local_score_marginal_general(Data, Xi, PAi, parameters)
```

### Parameters

**Data**: (sample, features).

**Xi**: current index.

**PAi**: parent indexes.

**parameters**: None.

### Returns

**score**: Local score.

## Generalized score with marginal likelihood for multi-dimensional variables

Calculate the local score by negative marginal likelihood, based on a regression model in RKHS for data with multi-dimensional variables [1].

### Usage

```
from causallearn.score.LocalScoreFunction import local_score_marginal_multi
score = local_score_marginal_multi(Data, Xi, PAi, parameters)
```

### Parameters

**Data**: (sample, features).

**Xi**: current index.

**PAi**: parent indexes.

**parameters**:dlabel: indicate the data dimensions that belong to each variable. It is only used when the variables have multivariate dimensions.

### Returns

**score**: Local score.