Module: meridian.analysis.review.results

Data structures for the Model Quality Checks results.

Classes

class BaseCase : Base class for all check cases.

class BaseResultData : Base class for check result data.

class BaselineCases : Cases for the Baseline Check.

class BaselineCheckResult : The immutable result of the Baseline Check.

class BayesianPPPCases : Cases for the Bayesian Posterior Predictive P-value Check.

class BayesianPPPCheckResult : The immutable result of the Bayesian Posterior Predictive P-value Check.

class ChannelResult : Base class for channel-level check results.

class CheckResult : Base class for model-level check results.

class ConvergenceCases : Cases for the Convergence Check.

class ConvergenceCheckResult : The immutable result of the Convergence Check.

class GoodnessOfFitCases : Cases for the Goodness of Fit Check.

class GoodnessOfFitCheckResult : The immutable result of the Goodness of Fit Check.

class ModelCheckCase : Base class for all model-level check cases.

class PriorPosteriorShiftAggregateCases : Cases for Prior-Posterior Shift Check aggregate result.

class PriorPosteriorShiftChannelCases : Cases for Prior-Posterior Shift Check per channel.

class PriorPosteriorShiftChannelResult : The result of Prior-Posterior Shift Check for a single channel.

class PriorPosteriorShiftCheckResult : The immutable result of model-level Prior-Posterior Shift Check.

class ROIConsistencyAggregateCases : Cases for ROI Consistency Check aggregate result.

class ROIConsistencyChannelCases : Cases for ROI Consistency Check per channel.

class ROIConsistencyChannelResult : The immutable result of ROI Consistency Check for a single channel.

class ROIConsistencyCheckResult : The immutable result of model-level ROI Consistency Check.

class ReviewSummary : The final summary of all model quality checks.

class Status : Create a collection of name/value pairs.

NOT_CONVERGED_RECOMMENDATION
('We recommend increasing MCMC iterations or investigating model ' 'misspecification (e.g., priors, multicollinearity) before proceeding.')
NOT_FULLY_CONVERGED_RECOMMENDATION
('Manually inspect the parameters with high R-hat values to determine if the ' 'results are acceptable for your use case, and consider increasing MCMC ' 'iterations or investigating model misspecification.')

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