bristlecone
ProfileLikelihood Module
Given a maximum likelihood estimate (MLE), the profile likelihood method runs a Monte Carlo algorithm that samples around the MLE.
The range for each parameter is discovered at 95% and 68% confidence based on a chi squared distribution.
Types
| Type | Description |
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EstimateFunction<'modelTimeUnit, 'state, 'subject, 'date, 'timeunit, 'timespan> |
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Functions and values
| Function or value |
Description
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Full Usage:
interval nParam mle limit trace
Parameters:
int
mle : float<MeasureProduct<-logL, MeasureOne>>
limit : float<MeasureProduct<-logL, MeasureOne>>
trace : (float<MeasureProduct<-logL, MeasureOne>> * float<MeasureProduct<parameter, MeasureOne>> array) list
Returns: (float<MeasureProduct<parameter, MeasureOne>> * float<MeasureProduct<parameter, MeasureOne>>)[]
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Full Usage:
profile fit engine subject hypothesis n result
Parameters:
EstimationEngine<'a, 'b, 'u, 'v> -> EndCondition -> 'c -> ModelSystem<'modelTimeUnit> -> EstimationResult<'d, 'e, 'f>
engine : EstimationEngine<'a, 'b, 'u, 'v>
subject : 'c
hypothesis : ModelSystem<'modelTimeUnit>
n : int<MeasureProduct<iteration, MeasureOne>>
result : EstimationResult<'g, 'h, 'i>
Returns: Map<ShortCode, ConfidenceInterval>
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The profile likelihood method samples the likelihood space around the Maximum Likelihood Estimate
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