# Continuous Generates a continuous distribution to fit the underlying data. This generator can be linked to other Continuous generators to create multivariate distributions and can be partitioned by other columns. ## Characteristics


Consistency	No, cannot be made consistent.
Linking	Yes, can be linked.
Differential privacy	Configurable
Data-free	No
Allowed for primary keys	No
Allowed for unique columns	No
Uses format-preserving encryption (FPE)	No
Privacy ranking	2 if differential privacy enabled 3 if differential privacy not enabled
Generator ID (for the API)	`GaussianGenerator`

## How to configure To configure the generator: 1. From the **Link To** drop-down list, select the other Continuous generator columns to link to.\ \ The linking creates a multivariate distribution. 2. From the **Partition By** drop-down list, select one or more columns to use to partition the data.\ \ The selected columns must have the generator set to either Passthrough or Categorical.\ \ For more information about partitioning and how it works, go to [partitioning](https://docs.tonic.ai/app/generation/generators/generator-characteristics/partitioning "mention"). 3. Toggle the **Differential Privacy** setting to indicate whether to make the output data differentially private.\ \ By default, the generator is not differentially private. 4. If [Structural data encryption](https://docs.tonic.ai/app/generation/generators-assign-config/generators-data-encryption-config) is enabled, then to use it for this column, in the advanced options section, toggle **Use data encryption process** to the on position.