| class ExponentialPrior( LaplacePrior ) | [source] |
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Exponential prior distribution.
Pr( x ) = exp( -x / scale )
By default scale = 1.
The domain is [0,+Inf]. In computational practice the domain is limited to about [0,36] scale units
Wrapper for LaplacePrior( center=0, scale=scale, limits=[0, hilim] )
Examples
pr = ExponentialPrior() # scale=1.0
pr = ExponentialPrior( scale=5.0 ) # scale=5
Attributes
- scale : float
scale of the exponential
Attributes from Prior
lowLimit, highLimit, deltaP, _lowDomain, _highDomain
Author: Do Kester.
| ExponentialPrior( scale=1.0, hilimit=math.inf, prior=None ) | [source] |
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Constructor.
Parameters
- scale : float
of the exponential - hilimit : float
high limit - prior : ExponentialPrior
prior to copy (with new scale if applicable)
| copy( ) | [source] |
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| shortName( ) | [source] |
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Return ExponentialPrior.
| Methods inherited from LaplacePrior |
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| Methods inherited from Prior |
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- limitedIntegral( center=0, circular=False, limits=None )
- setLimits( limits=None )
- setPriorAttributes( limits, circular )
- isCircular( )
- limitedDomain2Unit( dval )
- limitedUnit2Domain( uval )
- circularDomain2Unit( dval )
- circularUnit2Domain( uval )
- unsetLimits( )
- setAttributes( limits=None, scale=None )
- isOutOfLimits( par )
- checkLimit( par )
- stayInLimits( par )
- hasLowLimit( )
- hasHighLimit( )
- hasLimits( )
- getLimits( )
- getIntegral( )
- getRange( )
- partialDomain2Unit( p )
- numPartialDomain2Unit( dval )
- numPartialLog( p )