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# Prior Object

A prior belief distribution of a Parameter. By default, SigOpt assumes the parameter to be uniformly distributed. SigOpt allows users to specify the following distributions on `double` parameters. Refer to the Prior Beliefs documentation for more information.

### Beta Prior

SigOpt implements the generalized Beta distribution, which normalizes the Beta distribution to the parameter bounds.

### Normal Prior

SigOpt implements the truncated Normal distribution, which truncates the Normal distribution to the parameter bounds.

## Fields

Key
Type
Value
`mean`
`float`
Only supported for normal prior. Mean of the truncated Normal distribution.
`name`
`string`
The name of the prior distribution. Currently only supports beta and normal priors.
`scale`
`float`
Only supported for normal prior. Standard deviation of the truncated Normal distribution.
`shape_a`
`float`
Only supported for beta prior. Shape parameter α of the Beta distribution.
`shape_b`
`float`
Only supported for beta prior. Shape parameter β of the Beta distribution.

## Examples

### Beta Prior

{
"name": "beta",
"object": "beta_prior",
"shape_a": 2,
"shape_b": 4.5
}

### Normal Prior

{
"name": "normal",
"object": "normal_prior",
"mean": 0.5,
"scale": 1.2
}