#include <StatisticManager.h>

Public Attributes
std::map< ParamId, MarginalType >	override_nuisance_marginals {}
	Per-parameter overrides for nuisance marginal laws.

std::map< ExperimentObs, MarginalType >	override_exp_data_marginals {}
	Per-observable overrides for experimental-data marginals.

CopulaType	nuisance_copula_type = CopulaType::GAUSSIAN
	Copula used to correlate nuisance parameters.

CopulaType	exp_data_copula_type = CopulaType::GAUSSIAN
	Copula used to correlate experimental observables.

std::size_t	MLE_max_iter = 500
	Maximum number of minimizer function calls/iterations.

double	MLE_tol = 1e-8
	Minimizer tolerance passed to the backend.

unsigned	MLE_strategy = 2
	Backend minimization strategy; zero means backend default where supported.

bool	MLE_run_hesse = true
	Whether to request HESSE/covariance estimation after the fit.

bool	MLE_request_minos = false
	Whether to request MINOS errors when supported by the backend build.

bool	MLE_verbose = false
	Enables verbose output from the fit backend.

double	nuisance_relevance_cutoff = 1e-8
	Relative-uncertainty cutoff for the first nuisance preselection pass.

bool	nuisance_sensitivity_pruning = true
	Enables local model-sensitivity pruning of nuisance candidates.

double	nuisance_sensitivity_probe_sigmas = 1.0
	Size of the +/- finite-difference probe in units of nuisance sigma.

double	nuisance_sensitivity_rel_cutoff = 1e-6
	Relative observable shift required to keep a nuisance.

double	nuisance_sensitivity_abs_cutoff = 1e-12
	Absolute observable shift required to keep a nuisance.

double	nuisance_sensitivity_scale_floor = 1e-3
	Lower scale used when normalizing relative observable shifts.

int	nuisance_sensitivity_contexts = 2
	Number of contexts tested by sensitivity pruning; negative disables the check.

double	nuisance_sensitivity_context_sigma = 0.35
	Randomized-context spread in nuisance sigma units.

unsigned	nuisance_sensitivity_seed = 12345
	RNG seed used to build sensitivity-pruning contexts.

bool	nuisance_sensitivity_keep_on_failure = true
	Keeps a nuisance if its sensitivity probe fails.

bool	fit_parameter_sensitivity_check = true
	Reject fit parameters that do not measurably change any selected observable.

double	fit_parameter_sensitivity_probe_fraction = 0.05
	Minimum probe size as a fraction of explicit/default fit bounds.

double	fit_parameter_sensitivity_rel_cutoff = 1e-10
	Relative observable shift required to regard a fit parameter as active.

double	fit_parameter_sensitivity_abs_cutoff = 1e-12
	Absolute observable shift required to regard a fit parameter as active.

bool	fit_parameter_sensitivity_keep_on_failure = true
	Keeps a fit parameter when its sensitivity probe cannot be evaluated safely.

bool	MLE_trace_first_evals = false
	Enables debug tracing of the first likelihood evaluations.

std::size_t	MLE_trace_max_evals = 25
	Maximum number of likelihood evaluations printed when tracing is enabled.

bool	MLE_allow_profile_hessian_fallback = true
	Allows numerical profile-Hessian covariance fallback if backend covariance fails.

double	MLE_profile_hessian_step_scale = 1.0
	Step scaling used by the numerical profile-Hessian fallback.

double	MLE_profile_hessian_eig_floor_rel = 1e-8
	Relative eigenvalue floor used to regularize the fallback Hessian.

StatisticLikelihoodMode	likelihood_mode = StatisticLikelihoodMode::CHI2_MC_COVARIANCE
	Likelihood mode used by compute_MLE().

double	chi2_covariance_ridge_rel = 1e-8
	Relative diagonal ridge used before inverting chi-square covariance matrices.

double	chi2_covariance_ridge_abs = 1e-12
	Absolute diagonal ridge used before inverting chi-square covariance matrices.

bool	MC_force_decay_threads_to_one = true
	Give MC priority over internal decay parallelism.

std::size_t	MC_forced_decay_threads = 1
	Decay thread count while MC workers are running.

Detailed Description

Definition at line 68 of file StatisticManager.h.

Member Data Documentation

◆ chi2_covariance_ridge_abs

double AdvancedStatisticConfig::chi2_covariance_ridge_abs = 1e-12

Absolute diagonal ridge used before inverting chi-square covariance matrices.

Definition at line 106 of file StatisticManager.h.

◆ chi2_covariance_ridge_rel

double AdvancedStatisticConfig::chi2_covariance_ridge_rel = 1e-8

Relative diagonal ridge used before inverting chi-square covariance matrices.

Definition at line 105 of file StatisticManager.h.

◆ exp_data_copula_type

CopulaType AdvancedStatisticConfig::exp_data_copula_type = CopulaType::GAUSSIAN

Copula used to correlate experimental observables.

Definition at line 72 of file StatisticManager.h.

◆ fit_parameter_sensitivity_abs_cutoff

double AdvancedStatisticConfig::fit_parameter_sensitivity_abs_cutoff = 1e-12

Absolute observable shift required to regard a fit parameter as active.

Definition at line 95 of file StatisticManager.h.

◆ fit_parameter_sensitivity_check

bool AdvancedStatisticConfig::fit_parameter_sensitivity_check = true

Reject fit parameters that do not measurably change any selected observable.

Definition at line 92 of file StatisticManager.h.

◆ fit_parameter_sensitivity_keep_on_failure

bool AdvancedStatisticConfig::fit_parameter_sensitivity_keep_on_failure = true

Keeps a fit parameter when its sensitivity probe cannot be evaluated safely.

Definition at line 96 of file StatisticManager.h.

◆ fit_parameter_sensitivity_probe_fraction

double AdvancedStatisticConfig::fit_parameter_sensitivity_probe_fraction = 0.05

Minimum probe size as a fraction of explicit/default fit bounds.

Definition at line 93 of file StatisticManager.h.

◆ fit_parameter_sensitivity_rel_cutoff

double AdvancedStatisticConfig::fit_parameter_sensitivity_rel_cutoff = 1e-10

Relative observable shift required to regard a fit parameter as active.

Definition at line 94 of file StatisticManager.h.

◆ likelihood_mode

StatisticLikelihoodMode AdvancedStatisticConfig::likelihood_mode = StatisticLikelihoodMode::CHI2_MC_COVARIANCE

Likelihood mode used by compute_MLE().

Definition at line 104 of file StatisticManager.h.

◆ MC_force_decay_threads_to_one

bool AdvancedStatisticConfig::MC_force_decay_threads_to_one = true

Give MC priority over internal decay parallelism.

Definition at line 108 of file StatisticManager.h.

◆ MC_forced_decay_threads

std::size_t AdvancedStatisticConfig::MC_forced_decay_threads = 1

Decay thread count while MC workers are running.

Definition at line 109 of file StatisticManager.h.

◆ MLE_allow_profile_hessian_fallback

bool AdvancedStatisticConfig::MLE_allow_profile_hessian_fallback = true

Allows numerical profile-Hessian covariance fallback if backend covariance fails.

Definition at line 100 of file StatisticManager.h.

◆ MLE_max_iter

std::size_t AdvancedStatisticConfig::MLE_max_iter = 500

Maximum number of minimizer function calls/iterations.

Definition at line 74 of file StatisticManager.h.

◆ MLE_profile_hessian_eig_floor_rel

double AdvancedStatisticConfig::MLE_profile_hessian_eig_floor_rel = 1e-8

Relative eigenvalue floor used to regularize the fallback Hessian.

Definition at line 102 of file StatisticManager.h.

◆ MLE_profile_hessian_step_scale

double AdvancedStatisticConfig::MLE_profile_hessian_step_scale = 1.0

Step scaling used by the numerical profile-Hessian fallback.

Definition at line 101 of file StatisticManager.h.

◆ MLE_request_minos

bool AdvancedStatisticConfig::MLE_request_minos = false

Whether to request MINOS errors when supported by the backend build.

Definition at line 78 of file StatisticManager.h.

◆ MLE_run_hesse

bool AdvancedStatisticConfig::MLE_run_hesse = true

Whether to request HESSE/covariance estimation after the fit.

Definition at line 77 of file StatisticManager.h.

◆ MLE_strategy

unsigned AdvancedStatisticConfig::MLE_strategy = 2

Backend minimization strategy; zero means backend default where supported.

Definition at line 76 of file StatisticManager.h.

◆ MLE_tol

double AdvancedStatisticConfig::MLE_tol = 1e-8

Minimizer tolerance passed to the backend.

Definition at line 75 of file StatisticManager.h.

◆ MLE_trace_first_evals

bool AdvancedStatisticConfig::MLE_trace_first_evals = false

Enables debug tracing of the first likelihood evaluations.

Definition at line 98 of file StatisticManager.h.

◆ MLE_trace_max_evals

std::size_t AdvancedStatisticConfig::MLE_trace_max_evals = 25

Maximum number of likelihood evaluations printed when tracing is enabled.

Definition at line 99 of file StatisticManager.h.

◆ MLE_verbose

bool AdvancedStatisticConfig::MLE_verbose = false

Enables verbose output from the fit backend.

Definition at line 79 of file StatisticManager.h.

◆ nuisance_copula_type

CopulaType AdvancedStatisticConfig::nuisance_copula_type = CopulaType::GAUSSIAN

Copula used to correlate nuisance parameters.

Definition at line 71 of file StatisticManager.h.

◆ nuisance_relevance_cutoff

double AdvancedStatisticConfig::nuisance_relevance_cutoff = 1e-8

Relative-uncertainty cutoff for the first nuisance preselection pass.

Definition at line 81 of file StatisticManager.h.

◆ nuisance_sensitivity_abs_cutoff

double AdvancedStatisticConfig::nuisance_sensitivity_abs_cutoff = 1e-12

Absolute observable shift required to keep a nuisance.

Definition at line 85 of file StatisticManager.h.

◆ nuisance_sensitivity_context_sigma

double AdvancedStatisticConfig::nuisance_sensitivity_context_sigma = 0.35

Randomized-context spread in nuisance sigma units.

Definition at line 88 of file StatisticManager.h.

◆ nuisance_sensitivity_contexts

int AdvancedStatisticConfig::nuisance_sensitivity_contexts = 2

Number of contexts tested by sensitivity pruning; negative disables the check.

Definition at line 87 of file StatisticManager.h.

◆ nuisance_sensitivity_keep_on_failure

bool AdvancedStatisticConfig::nuisance_sensitivity_keep_on_failure = true

Keeps a nuisance if its sensitivity probe fails.

Definition at line 90 of file StatisticManager.h.

◆ nuisance_sensitivity_probe_sigmas

double AdvancedStatisticConfig::nuisance_sensitivity_probe_sigmas = 1.0

Size of the +/- finite-difference probe in units of nuisance sigma.

Definition at line 83 of file StatisticManager.h.

◆ nuisance_sensitivity_pruning

bool AdvancedStatisticConfig::nuisance_sensitivity_pruning = true

Enables local model-sensitivity pruning of nuisance candidates.

Definition at line 82 of file StatisticManager.h.

◆ nuisance_sensitivity_rel_cutoff

double AdvancedStatisticConfig::nuisance_sensitivity_rel_cutoff = 1e-6

Relative observable shift required to keep a nuisance.

Definition at line 84 of file StatisticManager.h.

◆ nuisance_sensitivity_scale_floor

double AdvancedStatisticConfig::nuisance_sensitivity_scale_floor = 1e-3

Lower scale used when normalizing relative observable shifts.

Definition at line 86 of file StatisticManager.h.

◆ nuisance_sensitivity_seed

unsigned AdvancedStatisticConfig::nuisance_sensitivity_seed = 12345

RNG seed used to build sensitivity-pruning contexts.

Definition at line 89 of file StatisticManager.h.

◆ override_exp_data_marginals

std::map<ExperimentObs, MarginalType> AdvancedStatisticConfig::override_exp_data_marginals {}

Per-observable overrides for experimental-data marginals.

Definition at line 70 of file StatisticManager.h.

◆ override_nuisance_marginals

std::map<ParamId, MarginalType> AdvancedStatisticConfig::override_nuisance_marginals {}

Per-parameter overrides for nuisance marginal laws.

Definition at line 69 of file StatisticManager.h.

The documentation for this struct was generated from the following file:

/home/runner/work/Hyperiso/Hyperiso/Hyperiso/Hyperiso/core/src/Statistic/domain/StatisticManager.h

Public Attributes