Package | Description |
---|---|
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.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
|
Modifier and Type | Interface and Description |
---|---|
interface |
DefaultReportable |
interface |
FigureReportable |
interface |
ObjectReportable |
Modifier and Type | Interface and Description |
---|---|
interface |
OdeSolution
Algorithms designed to solve ODE's must implment this interface.
|
interface |
StochasticOdeSolution
This interface extends the interface for non-stochastic ODE's for stochastic
ODE's.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractOdeSolver
General Ode numerical integrator.
|
class |
AbstractOdeUpdater |
class |
DefaultOdeSolver |
class |
EulerOdeUpdater |
class |
OdeModel
This model wraps an OdeSolver and extends the StatisticalModel.
|
class |
OdeSolver
Decorator class for ODE algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractProposalDistribution
A standard approach to the proposal distribution called for in Metropolis-Hastings Markov Chain
Monte-Carlo.
|
class |
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.
|
class |
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.
|
class |
GaussianProposal
A convenience class for setting up a proposal distribution which
is Gaussian for all parameters in a companion StatisticalModel.
|
class |
MCMC |
class |
StatisticalModel
This is a class which implements NamedParameters can make predictions as a function of those parameters
and can have its parameters optimized.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractDiffuse |
class |
CrankNicholson
Sparse matrix implementation of Crank-Nicholson parabolic equation solver.
|
class |
DefaultDiffuse |
Modifier and Type | Class and Description |
---|---|
class |
FCDF |
class |
NormPDF |
Modifier and Type | Class and Description |
---|---|
class |
Constant |
class |
Cubic |
class |
HollingI |
class |
HollingII |
class |
HollingIII |
class |
Linear |
class |
MichaelisMenten |
class |
Quadratic |
Modifier and Type | Class and Description |
---|---|
class |
AbstractGammaAlgorithm
Gamma function evaluation.
|
class |
AbstractIncBetaAlgorithm
Incomplete Beta function.
|
class |
AbstractLogGammaAlgorithm
Gamma function evaluation.
|
class |
NRIncBetaAlgorithm
Algorithm is based on Numerical Recipies in Fortran p.220-221.
|
class |
NRLogGammaAlgorithm
Algorithm is based on Numerical Recipies in Fortran.
|
class |
TothGammaAlgorithm
Algorithm is based on an approximation presented by Viktor T.
|
Modifier and Type | Class and Description |
---|---|
class |
XppOdeStatisticalModel |
Copyright © 2011, 2013. Daniel P. Dougherty