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**mcplR**: Multiple Cue Probability Learning in R**ConstraintsList-class**: Parameter constraints

# Parameter constraints

### Description

Objects of this class represent parameter constraints. Currently, two types of constraints are implemented: box constraints, and linear constraints. The class Unconstrained is used when there are no constraints.

### Author(s)

Maarten Speekenbrink

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- AICc: Corrected Akaike Information Criterion
- AICc: Corrected Akaike Information Criterion
- ALCOVE: Attention Learning COVEring map model (ALCOVE)
- ALCOVE: Attention Learning COVEring map model (ALCOVE)
- ALCOVElearning: Attention Learning COVEring map model (ALCOVE)
- ALCOVElearning: Attention Learning COVEring map model (ALCOVE)
- canRepar-methods: Reparametrization methods
- canRepar-methods: Reparametrization methods
- ConstraintsList-class: Parameter constraints
- ConstraintsList-class: Parameter constraints
- fit-methods: Fit a model (estimate model parameters).
- fit-methods: Fit a model (estimate model parameters).
- GaussianMixtureResponse: Generate a Gaussian Mixture Response model
- GaussianMixtureResponse: Generate a Gaussian Mixture Response model
- GaussianMixtureResponse-class: Class "GaussianMixtureResponse"
- GaussianMixtureResponse-class: Class "GaussianMixtureResponse"
- GaussianResponse-class: Class "GaussianResponse"
- GaussianResponse-class: Class "GaussianResponse"
- gcm: Generalized Context Model
- gcm: Generalized Context Model
- ggcm: generalized Generalized Context Model
- ggcm: generalized Generalized Context Model
- GlmResponse: Generate a Generalized Linear Model (GLM) Response model
- GlmResponse: Generate a Generalized Linear Model (GLM) Response model
- GlmResponse-class: Class "GlmResponse"
- GlmResponse-class: Class "GlmResponse"
- MaxResponse: Maximising responses with error
- MaxResponse: Maximising responses with error
- MaxResponse-class: Class "MaxResponse"
- MaxResponse-class: Class "MaxResponse"
- McplBaseModel: Class "McplBaseModel"
- McplBaseModel: Class "McplBaseModel"
- McplModel: McplModel
- McplModel: McplModel
- McplModel-class: Class "McplModel"
- McplModel-class: Class "McplModel"
- mcplR: mcplR: Multiple Cue Probability Learning models in R
- mcplR: mcplR: Multiple Cue Probability Learning models in R
- mcplr-internal: mcplR internal functions, methods and classes.
- mcplr-internal: mcplR internal functions, methods and classes.
- ParStruct: Parameter structure objects
- ParStruct: Parameter structure objects
- ParStruct-class: Class "ParStruct"
- ParStruct-class: Class "ParStruct"
- RatioRuleResponse-class: Class "RatioRuleResponse"
- RatioRuleResponse-class: Class "RatioRuleResponse"
- rescorlaWagner: Rescorla-Wagner Model
- rescorlaWagner: Rescorla-Wagner Model
- Rsq: R-Squared
- Rsq: R-Squared
- runm-methods: Run a model over the data.
- runm-methods: Run a model over the data.
- simulate: simulate
- simulate: simulate
- slfn: Single Layer Feedforward Network
- slfn: Single Layer Feedforward Network
- SMPT: Stock Market Prediction Task
- SMPT: Stock Market Prediction Task
- WPT: Weather Prediction Task data
- WPT: Weather Prediction Task data