ScaledErrorDistribution = class ScaledErrorDistribution(ErrorDistribution) |
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ScaledErrorDistribution(scale=1.0, limits=None, fixed=None, copy=None)
Base class that defines methods common to error distributions with a scale.
GaussErrorDistribution
LaplaceErrorDistribution
CauchyErrorDistribution
ExponentialErrorDistribution
UniformErrorDistribution
Author Do Kester. |
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- Method resolution order:
- ScaledErrorDistribution
- ErrorDistribution
- builtins.object
Constructor:
- ScaledErrorDistribution( scale=1.0, limits=None, fixed=None, copy=None )
- Default Constructor.
Parameters
----------
scale : float
noise scale
limits : None or list of 2 floats [low,high]
None : no limits implying fixed scale
low low limit on scale (needs to be >0)
high high limit on scale
when limits are set, the scale is to be fitted
fixed : dictionary of {int:float}
int list if parameters to fix permanently. Default None.
float list of values for the fixed parameters.
copy : ScaledErrorDistribution
distribution to be copied.
Methods defined here:
- copy()
- Return copy of this.
- setLimits( limits )
- Set limits for scale.
Parameters
----------
limits : [low,high]
low : float or array_like
low limits
high : float or array_like
high limits
Methods inherited from ErrorDistribution:
- acceptWeight()
- domain2Unit( dval, ks )
- getChisq( problem, allpars=None )
- getGaussianScale( problem, allpars=None )
- getResiduals( problem, allpars=None )
- hyparname( k )
- isBound()
- keepFixed( fixed=None )
- logCLhood( problem, allpars )
- logLhood( problem, allpars )
- numPartialLogL( problem, allpars, fitIndex )
- partialLogL( problem, allpars, fitIndex )
- partialLogL_alt( problem, allpars, fitIndex )
- setPriors( priors )
- setResult()
- toSigma( scale )
- unit2Domain( uval, ks )
- updateLogL( problem, allpars, parval=None )
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