| Package | Description |
|---|---|
| com.mockturtlesolutions.snifflib.datatypes |
Contains standard classes and interfaces for storage, retrieval, and display.
|
| com.mockturtlesolutions.snifflib.graphics |
Contains standard classes and interfaces for 2D and 3D graphics.
|
| com.mockturtlesolutions.snifflib.integration |
Contains standard classes and interfaces for performing integration.
|
| com.mockturtlesolutions.snifflib.invprobs |
Contains standard classes and interfaces for solving statistical inverse problems.
|
| com.mockturtlesolutions.snifflib.pde |
Contains standard classes and interfaces for numerical solution of partial differential equations.
|
| com.mockturtlesolutions.snifflib.statmodeltools.database |
Base classes for the repository storage framework of the statmodeltools package.
|
| com.mockturtlesolutions.snifflib.statmodeltools.workbench |
Graphical interface classes for the repository storage framework of the statmodeltools package.
|
| com.mockturtlesolutions.snifflib.stats |
Contains standard classes and interfaces for statistical storage classes and algorithms.
|
| com.mockturtlesolutions.snifflib.testfun |
Contains some typical functions useful for testing various algorithms.
|
| com.mockturtlesolutions.snifflib.util |
Contains some utility classes providing methods of broad applicability.
|
| com.mockturtlesolutions.snifflib.xppauttools.database |
Base classes for the repository storage framework of xppauttools
|
| Class and Description |
|---|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| Lpreg |
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| DeclaredParameters |
| DeclaredVariables |
| GraphicalStatisticalModel
Provides a graphical wrapper for the StatisticalModel.
|
| Likelihood
Classes implementing this interface can return likelihood.
|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| VectorValued |
| Class and Description |
|---|
| AbstractBandwidthMethod |
| AbstractCalibrationDialog |
| AbstractProposalDistribution
A standard approach to the proposal distribution called for in Metropolis-Hastings Markov Chain
Monte-Carlo.
|
| AbstractSmoothMethod |
| AbstractWeightAlgorithm
Abstract class for kernel -based weight functions.
|
| BandwidthMethod |
| CalibrationPanel |
| DblParamSetEditor
Allows editing of the values of a DblParameterSet.
|
| DblParamSetSimplex
When doing Simplex optimization it is important to avoid doing lots of sorting.
|
| Dbracket
Class useful for finding and returning bracketing sets for sorted vectors.
|
| DeclaredParameters |
| DeclaredVariables |
| DiffEvolConfiguration |
| HierarchicalNode |
| HierarchicalParameters |
| InvProbConfiguration |
| Likelihood
Classes implementing this interface can return likelihood.
|
| Lpreg |
| LpregDiagnostics |
| MCMCBlock
Storage class for MCMC cycle block.
|
| MCMCSampler |
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| NMSimplexConfiguration |
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| Optimization |
| OptimizationEvent |
| OptimizationListener
Listener intended for optimization events.
|
| ParameterChangeEvent |
| ParameterChangeListener
Listener intended for changes in the parameters of a StatisticalModel.
|
| ParameterValueEditor |
| ParameterValuePair |
| ProposalDistribution |
| SimulatedAnnealing
Any optimization methods capable of simulated annealing should implement this interface.
|
| SmoothMethod |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| TricubeWeightAlgorithm
Tricube kernel weight function.
|
| VisualScalarOptimizer
This abstract class specifies the visuallyConfigure and visualDiagnostics methods
which any implementing subclass must implement giving visual (GUI) interface to the
optimizer.
|
| WeightAlgorithm
Kernel weight algorithm interface.
|
| Class and Description |
|---|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| Class and Description |
|---|
| DeclaredParameters |
| DeclaredVariables |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| DeclaredParameters |
| DeclaredVariables |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| DblParamSetEditor
Allows editing of the values of a DblParameterSet.
|
| DblParamSetFrame
Allows editing of the values of a DblParameterSet.
|
| DeclaredParameters |
| DeclaredVariables |
| Likelihood
Classes implementing this interface can return likelihood.
|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| DeclaredParameters |
| DeclaredVariables |
| Likelihood
Classes implementing this interface can return likelihood.
|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| AbstractSimplexObjective |
| DeclaredParameters |
| DeclaredVariables |
| Likelihood
Classes implementing this interface can return likelihood.
|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| Class and Description |
|---|
| DeclaredParameters |
| DeclaredVariables |
| Likelihood
Classes implementing this interface can return likelihood.
|
| NamedParameters
NamedParameters is an interface for models and other objects that have parameters.
|
| ObjectSampler
Provides methods for classes wishing to generate samples of objects.
|
| ObjectSamplerClient |
| OptimizableScalar |
| StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
Copyright © 2011, 2013. Daniel P. Dougherty