See: Description
| Interface | Description |
|---|---|
| BandwidthMethod | |
| DeclaredParameters | |
| DeclaredVariables | |
| HierarchicalParameters | |
| InitialConditionSource | |
| Likelihood |
Classes implementing this interface can return likelihood.
|
| MCMCSampler | |
| 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 | |
| Optimizable | |
| OptimizableScalar | |
| Optimization | |
| OptimizationListener |
Listener intended for optimization events.
|
| ParameterChangeListener |
Listener intended for changes in the parameters of a StatisticalModel.
|
| PenalizedLikelihood |
Classes implementing this interface can return posterior probability.
|
| PosteriorProbability |
Classes implementing this interface can return posterior probability.
|
| PriorProbability |
Classes implementing this interface can return prior probability.
|
| ProposalDistribution | |
| SimulatedAnnealing |
Any optimization methods capable of simulated annealing should implement this interface.
|
| SmoothMethod | |
| SumOfSquares |
Classes implementing this interface can return sum of squares.
|
| VectorValued | |
| WeightAlgorithm |
Kernel weight algorithm interface.
|
| Class | Description |
|---|---|
| AbstractBandwidthMethod | |
| AbstractCalibrationDialog | |
| AbstractProposalDistribution |
A standard approach to the proposal distribution called for in Metropolis-Hastings Markov Chain
Monte-Carlo.
|
| AbstractSimplexObjective | |
| AbstractSmoothMethod | |
| AbstractWeightAlgorithm |
Abstract class for kernel -based weight functions.
|
| BatesWatts |
BatesWatts measures of non-linearity and related statistics.
|
| BayesianLinear |
This is a simple extension of Linear appropriate for full Bayesian linear regression
under the assumption of independent and identically distributed Gaussian errors and
uniform prior.
|
| BiweightWeightAlgorithm |
Biweight kernel weight function.
|
| CalibrationPanel | |
| DblParamSetEditor |
Allows editing of the values of a DblParameterSet.
|
| DblParamSetFrame |
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.
|
| DefaultInitialConditionSource | |
| DiffEvol |
Differential evolution Genetic Algorithm.
|
| DiffEvolConfiguration | |
| DistributedStatisticalModel |
Provides a transparent extension of StatisticalModel for cases where parameters and/or data may be distributed
across one or more other classes (e.g.
|
| EpanechnikovWeightAlgorithm |
Epanechnikov kernel weight function.
|
| FixedSmoothMethod | |
| GaussianProposal |
A convenience class for setting up a proposal distribution which
is Gaussian for all parameters in a companion StatisticalModel.
|
| GCVSmoothMethod | |
| GraphicalStatisticalModel |
Provides a graphical wrapper for the StatisticalModel.
|
| GraphicalStatisticalModelBeanInfo | |
| GraphicalStatisticalModelPersistenceDelegate | |
| HierarchicalCellEditor | |
| HierarchicalCellRenderer | |
| HierarchicalEditor |
A tree-based editor for
|
| HierarchicalNode | |
| HierarchyTree | |
| HierarchyTreeNode | |
| Interp1D |
Class for performing polynomial interpolation (or extrapolation) with error estimation.
|
| InvProbConfiguration | |
| KernelDensityEstimator | |
| LeastSquaresCalibrationPanel | |
| Lpreg | |
| LpregDiagnostics | |
| MCMC | |
| MCMCBlock |
Storage class for MCMC cycle block.
|
| MCMCDemo | |
| MCMCDemoFrame | |
| MCMCDialog | |
| MethodStorage |
Stores information about methods and their arguments.
|
| MetropolisHastings | |
| MyQuadratic | |
| NMSimplex | |
| NMSimplexConfiguration | |
| NNBandwidth | |
| NormalWeightAlgorithm |
Normal kernel weight function.
|
| OptimizationEvent | |
| ParameterChangeEvent | |
| ParameterValueEditor | |
| ParameterValuePair | |
| Polint |
Polynomial interpolation or extrapolation with error estimates.
|
| Pzextr |
Update-able polynomial extrapolation to zero.
|
| ScalarRootLocator |
Locate the root of a function of a single variable by searching between an upper and lower bound.
|
| StatisticalModel |
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
| StatisticalModelBeanInfo | |
| StatisticalModelPersistenceDelegate | |
| StdRobustWeightAlgorithm | |
| test_simplex | |
| TricubeWeightAlgorithm |
Tricube kernel weight function.
|
| TriweightWeightAlgorithm |
Triweight kernel weight function.
|
| UniformWeightAlgorithm |
Uniform 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.
|
| Weight |
Basic decorator class for doing various operations associated with kernel weights.
|
| Exception | Description |
|---|---|
| FunctionEvaluationException | |
| SnifflibInvprobsException |
Copyright © 2011, 2013. Daniel P. Dougherty