Convergence Module
Convergence diagnostics for monte-carlo markov chain (MCMC) analyses.
Types
| Type | Description |
|
A per-parameter convergence statistic. The statistic used is given in `StatisticName`. |
Functions and values
| Function or value |
Description
|
Full Usage:
gelmanRubin nMostRecent subjectId hypothesisId result
Parameters:
int
-
How many recent iterations to use from the trace.
subjectId : string
-
The subject identifier
hypothesisId : string
-
The hypothesis identifier
result : ResultSet<'subject, 'hypothesis, 'date, 'timeunit, 'timespan>
-
A result set (of 1 .. many results) for a particular subject and hypothesis
Returns: ConvergenceStatistic seq option
If more than one replicate, the R-hat convergence statistic across replicates
|
Calculate the Gelman-Rubin statistic for each parameter in the given `ResultSet`. The statistic tends downwards to one, with one indicating perfect convergence between all chains.
|
Full Usage:
gelmanRubinAll nMostRecent subject hypothesis results
Parameters:
int
-
How many recent iterations to use from the trace.
subject : 'subject -> string
-
A function to retrieve a subject ID from a subject
hypothesis : 'hypothesis -> string
-
A function to retrieve a hypothesis ID from a hypothesis
results : ResultSet<'subject, 'hypothesis, 'date, 'timeunit, 'timespan> seq
Returns: ConvergenceStatistic seq
If more than one replicate, the R-hat convergence statistic across replicates
|
Calculate the Gelman-Rubin statistic for each parameter in all of the given `ResultSet`. The statistic tends downwards to one, with one indicating perfect convergence between all chains.
|
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