biogeme.latent_variables.resolved module

class biogeme.latent_variables.resolved.CutpointKind(*values)[source]

Bases: str, Enum

DERIVED = 'derived'
FIXED = 'fixed'
FREE = 'free'
class biogeme.latent_variables.resolved.MeasurementErrorDistribution(*values)[source]

Bases: str, Enum

GAUSSIAN = 'gaussian'
LOGISTIC = 'logistic'
class biogeme.latent_variables.resolved.ParameterCreationKind(*values)[source]

Bases: str, Enum

BOUNDED_BETA = 'bounded_beta'
FIXED_BETA = 'fixed_beta'
FREE_BETA = 'free_beta'
LOG_EXP_BETA = 'log_exp_beta'
NUMERIC_CONSTANT = 'numeric_constant'
class biogeme.latent_variables.resolved.ParameterRole(*values)[source]

Bases: str, Enum

MEASUREMENT_INTERCEPT = 'measurement_intercept'
MEASUREMENT_LOADING = 'measurement_loading'
MEASUREMENT_SIGMA = 'measurement_sigma'
STRUCTURAL_COEFFICIENT = 'structural_coefficient'
STRUCTURAL_INTERCEPT = 'structural_intercept'
STRUCTURAL_SIGMA = 'structural_sigma'
THRESHOLD_DELTA = 'threshold_delta'
THRESHOLD_FIRST = 'threshold_first'
class biogeme.latent_variables.resolved.ParameterStatus(*values)[source]

Bases: str, Enum

FIXED = 'fixed'
FREE = 'free'
class biogeme.latent_variables.resolved.PositivityStrategy(*values)[source]

Bases: str, Enum

LOG_EXP = 'log_exp'
LOWER_BOUND = 'lower_bound'
NONE = 'none'
class biogeme.latent_variables.resolved.ResolvedConstant(value)[source]

Bases: object

Parameters:

value (float)

value: float
class biogeme.latent_variables.resolved.ResolvedCutpoint(symbol_name, kind, expression_text, source_parameter_names)[source]

Bases: object

Parameters:

  • symbol_name (str)

  • kind (CutpointKind)

  • expression_text (str)

  • source_parameter_names (list[str])

expression_text: str
kind: CutpointKind
source_parameter_names: list[str]
symbol_name: str
class biogeme.latent_variables.resolved.ResolvedLatentVariable(name, structural_equation, indicator_names, reference_indicator, normalization_notes)[source]

Bases: object

Parameters:

  • name (str)

  • structural_equation (ResolvedStructuralEquation)

  • indicator_names (list[str])

  • reference_indicator (str | None)

  • normalization_notes (list[str])

indicator_names: list[str]
name: str
normalization_notes: list[str]
reference_indicator: str | None
structural_equation: ResolvedStructuralEquation
class biogeme.latent_variables.resolved.ResolvedLinearCombination(intercept, terms)[source]

Bases: object

Parameters:
intercept: ResolvedParameterRef | ResolvedConstant | None
terms: list[ResolvedLinearTerm]
class biogeme.latent_variables.resolved.ResolvedLinearTerm(coefficient, variable_name)[source]

Bases: object

Parameters:
coefficient: ResolvedParameterRef | ResolvedConstant
variable_name: str
class biogeme.latent_variables.resolved.ResolvedMeasurementEquation(indicator_name, statement, type_name, measurement_model, systematic_part, sigma, observed_variable_name, threshold_system_name, error_distribution, normalization_notes)[source]

Bases: object

Parameters:
error_distribution: MeasurementErrorDistribution
indicator_name: str
measurement_model: MeasurementModel
normalization_notes: list[str]
observed_variable_name: str
sigma: ResolvedParameterRef | None
statement: str
systematic_part: ResolvedLinearCombination
threshold_system_name: str | None
type_name: str
class biogeme.latent_variables.resolved.ResolvedModel(metadata, latent_variables, measurement_equations, threshold_systems, parameters, normalization)[source]

Bases: object

Parameters:
free_parameters()[source]

Return the parameters that are estimated.

Fixed parameters and numeric constants are excluded because they do not appear in the estimation results. The order follows the insertion order of self.parameters.

Return type:

list[ResolvedParameter]

Returns:

list of free resolved parameters.

latent_variables: dict[str, ResolvedLatentVariable]
measurement_equations: dict[str, ResolvedMeasurementEquation]
metadata: ResolvedModelMetadata
normalization: ResolvedNormalizationSummary
parameters: dict[str, ResolvedParameter]
threshold_systems: dict[str, ResolvedThresholdSystem]
class biogeme.latent_variables.resolved.ResolvedModelMetadata(estimation_mode, measurement_models_present, has_gaussian, has_ordered_probit, has_ordered_logit, has_ordinal, n_latent_variables, n_indicators, n_threshold_systems)[source]

Bases: object

Parameters:

  • estimation_mode (EstimationMode)

  • measurement_models_present (list[MeasurementModel])

  • has_gaussian (bool)

  • has_ordered_probit (bool)

  • has_ordered_logit (bool)

  • has_ordinal (bool)

  • n_latent_variables (int)

  • n_indicators (int)

  • n_threshold_systems (int)

estimation_mode: EstimationMode
has_gaussian: bool
has_ordered_logit: bool
has_ordered_probit: bool
has_ordinal: bool
measurement_models_present: list[MeasurementModel]
n_indicators: int
n_latent_variables: int
n_threshold_systems: int
class biogeme.latent_variables.resolved.ResolvedNormalizationRule(scope, target_name, value, reason)[source]

Bases: object

Parameters:

  • scope (str)

  • target_name (str)

  • value (float | str)

  • reason (str)

reason: str
scope: str
target_name: str
value: float | str
class biogeme.latent_variables.resolved.ResolvedNormalizationSummary(rules, warnings, disclaimer)[source]

Bases: object

Parameters:
disclaimer: str
rules: list[ResolvedNormalizationRule]
warnings: list[str]
class biogeme.latent_variables.resolved.ResolvedParameter(semantic_ref, final_name, role, status, fixed_value, initial_value, lower_bound, upper_bound, positivity_strategy, creation_kind, notes=<factory>)[source]

Bases: object

Parameters:
creation_kind: ParameterCreationKind
final_name: str
fixed_value: float | None
initial_value: float
lower_bound: float | None
notes: list[str]
positivity_strategy: PositivityStrategy | None
role: ParameterRole
semantic_ref: ParameterRef | None
status: ParameterStatus
upper_bound: float | None
class biogeme.latent_variables.resolved.ResolvedParameterRef(final_name, semantic_ref=None)[source]

Bases: object

Parameters:
final_name: str
semantic_ref: ParameterRef | None
class biogeme.latent_variables.resolved.ResolvedStructuralEquation(latent_name, expression_name, systematic_part, sigma, draw_name, draw_type, error_distribution)[source]

Bases: object

Parameters:
draw_name: str
draw_type: str
error_distribution: str
expression_name: str
latent_name: str
sigma: ResolvedParameterRef | None
systematic_part: ResolvedLinearCombination
class biogeme.latent_variables.resolved.ResolvedThresholdSystem(type_name, symmetric, categories, neutral_labels, construction_kind, cutpoints, used_by_indicators, normalization_notes)[source]

Bases: object

Parameters:

  • type_name (str)

  • symmetric (bool)

  • categories (list[int])

  • neutral_labels (list[int])

  • construction_kind (ThresholdConstructionKind)

  • cutpoints (list[ResolvedCutpoint])

  • used_by_indicators (list[str])

  • normalization_notes (list[str])

categories: list[int]
construction_kind: ThresholdConstructionKind
cutpoints: list[ResolvedCutpoint]
neutral_labels: list[int]
normalization_notes: list[str]
symmetric: bool
type_name: str
used_by_indicators: list[str]
class biogeme.latent_variables.resolved.ThresholdConstructionKind(*values)[source]

Bases: str, Enum

MONOTONE = 'monotone'
SYMMETRIC = 'symmetric'