Reference·Classes

Class: Likelihood

Observation model for Bayesian inference: p(data | sim(theta)). Points at the observation holding the data and specifies the noise family + scale. name is the noise family (default Normal); source uses the same referencing as Observation.source, so the observed data can come from this experiment’s integration, an empirical network measure, or a runtime-bound array — one flexible hook, no data-loading path of its own. predicted names the other side of the residual when it differs from the data’s own observable.

URI: tvbo:Likelihood

 classDiagram
    class Likelihood
    click Likelihood href "./Likelihood.html"
      Likelihood : description
        
          
    
        
        
        Likelihood --> "0..1" String : description
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      Likelihood : name
        
          
    
        
        
        Likelihood --> "1" String : name
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      Likelihood : predicted
        
          
    
        
        
        Likelihood --> "*" String : predicted
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      Likelihood : sigma
        
          
    
        
        
        Likelihood --> "0..1" Float : sigma
        click Float href "../http://www.w3.org/2001/XMLSchema#float.html"
    

        
      Likelihood : source
        
          
    
        
        
        Likelihood --> "1..*" String : source
        click String href "../http://www.w3.org/2001/XMLSchema#string.html"
    

        
      

Class Properties

Property	Value
Class URI	tvbo:Likelihood

Slots

Name	Cardinality and Range	Description	Inheritance
name	1 xsd:string	Globally unique identifier for the entity	direct
description	0..1 xsd:string		direct
source	1..* xsd:string	Observation(s) providing the observed data, evaluated once at the declared co…	direct
predicted	* xsd:string	Observation(s) the model PREDICTS, recomputed for every proposed theta	direct
sigma	0..1 xsd:float	Observation-noise scale of the likelihood	direct

Usages

used by	used in	type	used
Inference	likelihood	range	Likelihood

Identifier and Mapping Information

Schema Source

• from schema: https://w3id.org/tvbo

Mappings

Mapping Type	Mapped Value
self	tvbo:Likelihood
native	tvbo:Likelihood

LinkML Source

Direct

name: Likelihood
description: 'Observation model for Bayesian inference: p(data | sim(theta)). Points
  at the observation holding the data and specifies the noise family + scale. `name`
  is the noise family (default Normal); `source` uses the same referencing as `Observation.source`,
  so the observed data can come from this experiment''s integration, an empirical
  network measure, or a runtime-bound array — one flexible hook, no data-loading path
  of its own. `predicted` names the other side of the residual when it differs from
  the data''s own observable.'
from_schema: https://w3id.org/tvbo
slots:
- name
- description
slot_usage:
  name:
    name: name
    ifabsent: string(Normal)
attributes:
  source:
    name: source
    description: Observation(s) providing the observed data, evaluated once at the
      declared configuration.
    from_schema: https://w3id.org/tvbo
    domain_of:
    - Panel
    - Edge
    - Observation
    - Dynamics
    - Parameter
    - CouplingInput
    - Likelihood
    - ResultBinding
    range: string
    required: true
    multivalued: true
  predicted:
    name: predicted
    description: 'Observation(s) the model PREDICTS, recomputed for every proposed
      theta. Defaults to `source`, which is right whenever the data enters from outside
      — a runtime-bound array or an empirical measure — because then the same observable
      serves both sides. Name it separately when the recording is itself declared
      in the forward pipeline: measurement noise applied to both sides is the same
      deterministic draw twice, so it cancels in the residual and the inference silently
      fits noiseless data.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Likelihood
    range: string
    multivalued: true
  sigma:
    name: sigma
    description: Observation-noise scale of the likelihood. May deliberately differ
      from the data's generative noise — it sets how tightly the likelihood constrains
      the (possibly degenerate) parameter ridge.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    domain_of:
    - Likelihood
    range: float
class_uri: tvbo:Likelihood

Induced

name: Likelihood
description: 'Observation model for Bayesian inference: p(data | sim(theta)). Points
  at the observation holding the data and specifies the noise family + scale. `name`
  is the noise family (default Normal); `source` uses the same referencing as `Observation.source`,
  so the observed data can come from this experiment''s integration, an empirical
  network measure, or a runtime-bound array — one flexible hook, no data-loading path
  of its own. `predicted` names the other side of the residual when it differs from
  the data''s own observable.'
from_schema: https://w3id.org/tvbo
slot_usage:
  name:
    name: name
    ifabsent: string(Normal)
attributes:
  source:
    name: source
    description: Observation(s) providing the observed data, evaluated once at the
      declared configuration.
    from_schema: https://w3id.org/tvbo
    owner: Likelihood
    domain_of:
    - Panel
    - Edge
    - Observation
    - Dynamics
    - Parameter
    - CouplingInput
    - Likelihood
    - ResultBinding
    range: string
    required: true
    multivalued: true
  predicted:
    name: predicted
    description: 'Observation(s) the model PREDICTS, recomputed for every proposed
      theta. Defaults to `source`, which is right whenever the data enters from outside
      — a runtime-bound array or an empirical measure — because then the same observable
      serves both sides. Name it separately when the recording is itself declared
      in the forward pipeline: measurement noise applied to both sides is the same
      deterministic draw twice, so it cancels in the residual and the inference silently
      fits noiseless data.'
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Likelihood
    domain_of:
    - Likelihood
    range: string
    multivalued: true
  sigma:
    name: sigma
    description: Observation-noise scale of the likelihood. May deliberately differ
      from the data's generative noise — it sets how tightly the likelihood constrains
      the (possibly degenerate) parameter ridge.
    from_schema: https://w3id.org/tvbo
    rank: 1000
    owner: Likelihood
    domain_of:
    - Likelihood
    range: float
  name:
    name: name
    description: Globally unique identifier for the entity.
    from_schema: https://w3id.org/tvbo/common
    slot_uri: schema:name
    ifabsent: string(Normal)
    identifier: true
    owner: Likelihood
    domain_of:
    - BrainAtlas
    - CommonCoordinateSpace
    - ParcellationEntity
    - StudyLayout
    - StudyTemplate
    - StudyDirectory
    - StudyFile
    - DBSProtocol
    - ClinicalScale
    - ClinicalScore
    - SoftwarePackage
    - SoftwareRequirement
    - SoftwareEnvironment
    - Figure
    - Event
    - Tractogram
    - ResultEntity
    - Activity
    - CachedArray
    - MeasureSpec
    - NamedArray
    - GraphGenerator
    - Binding
    - ProcedureStep
    - File
    - StateValue
    - Observation
    - Dynamics
    - StateVariable
    - Distribution
    - Parameter
    - CouplingInput
    - Argument
    - Function
    - FunctionCall
    - Callable
    - DerivedParameter
    - DerivedVariable
    - DataSource
    - OptimizationStage
    - Exploration
    - Inference
    - Prior
    - Likelihood
    - UpdateRule
    - Algorithm
    - Option
    - BranchSwitch
    - Continuation
    - Coupling
    - EnvironmentVariable
    - SchedulerDirective
    - Reducer
    range: string
    required: true
  description:
    name: description
    from_schema: https://w3id.org/tvbo
    rank: 1000
    slot_uri: dcterms:description
    owner: Likelihood
    domain_of:
    - CommonCoordinateSpace
    - Dataset
    - StudyLayout
    - StudyTemplate
    - StudyDirectory
    - StudyFile
    - ClinicalScore
    - SoftwarePackage
    - SoftwareRequirement
    - SoftwareEnvironment
    - Figure
    - Panel
    - Equation
    - Stimulus
    - Event
    - Tractogram
    - Matrix
    - ResultEntity
    - Activity
    - Phenotype
    - MeasureSpec
    - NamedArray
    - Network
    - GraphGenerator
    - ProcedureStep
    - File
    - Node
    - Edge
    - Observation
    - Dynamics
    - StateVariable
    - Parameter
    - CouplingInput
    - Argument
    - Function
    - FunctionCall
    - Callable
    - DerivedParameter
    - DerivedVariable
    - RandomStream
    - DataSource
    - OptimizationStage
    - Exploration
    - ExplorationAxis
    - FreeParameter
    - Inference
    - Prior
    - Likelihood
    - UpdateRule
    - AlgorithmStage
    - TuningObjective
    - Algorithm
    - BranchSwitch
    - Continuation
    - Integrator
    - Coupling
    - RegionMapping
    - SimulationExperiment
    - Study
    - ResultBinding
    - TimeSeries
    - NDArray
    - SpatialDomain
    - Mesh
    - SpatialField
    - FieldStateVariable
    - BoundaryCondition
    - PDESolver
    - PDE
    - Reducer
    range: string
class_uri: tvbo:Likelihood