-function probability density 
| AdaptiveRungeKutta | Adaptive Runge-Kutta method for solving a system of ordinary differential equations |
| AdditiveNoiseParticleResampler | Particle resampler with independent additive noise source |
| AuxiliaryParticleResampler | Auxiliary particle resampler |
| DensityTreeFactory | Factory for producing density tree nodes |
| DensityTreeInternal | Internal node of a density tree |
| DensityTreeLeaf | Leaf node of a density tree |
| DensityTreeMixturePdf | Density tree mixture probability density |
| DensityTreeNode | Node of a density tree |
| DensityTreeParticleResampler | Density tree particle resampler |
| DensityTreePdf | Probability density tree |
| DeterministicParticleResampler | Deterministic particle resampler |
| DifferentialModel | AdaptiveRungeKutta compatible model |
| DiracMixturePdf | Dirac mixture probability density |
| DiracPdf | Dirac -function probability density |
| Filter | Abstract filter |
| FixableStateModel | Model with fixable state variables |
| FunctionCollection | Collection of functions |
| FunctionModel | Function specification |
| GaussianKernel | Gaussian kernel for density estimation |
| GaussianMixturePdf | Gaussian mixture probability density |
| GaussianPdf | Multivariate Gaussian probability distribution |
| KalmanFilter | Kalman filter |
| KalmanFilterModel | KalmanFilter compatible model |
| KalmanSmoother | Kalman two-filter smoother |
| KalmanSmootherModel | KalmanSmoother compatible model |
| KDTree | KD (kernel density) tree based on Gray & Moore (2001) |
| KDTreeInternalNode | Internal node of a KD-tree |
| KDTreeLeafNode | Leaf node of a KD-tree |
| KDTreeNode | Node of a KD-tree |
| Kernel | Kernel for density estimation |
| LengthPartitioner | Partitions a set of weighted points into two sets at the midpoint of the widest dimension |
| LinearModel | Simple linear model |
| MixturePdf | Mixture probability density |
| MixturePdf::weighted_component | Weighted component |
| Norm | Vector norm |
| NumericalSolver | Abstract numerical solver for a system of differential equations |
| ParameterCollection | Collection of parameters |
| ParticleFilter | Particle filter |
| ParticleFilterModel | ParticleFilter compatible model |
| ParticleResampler | Resampler for particle filter |
| ParticleSmoother | Two-pass particle smoother |
| ParticleSmootherModel | ParticleSmoother compatible model |
| Partitioner | Partitions a set of weighted points into two sets for constructing a partition tree |
| PartitionTreeNode | Node of a spatial partition tree |
| Abstract probability distribution | |
| PNorm | Vector p-norm, |
| Random | Random numbers |
| RandomPartitioner | Partitions a set of weighted samples into two sets along the midpoint of a random dimension |
| RauchTungStriebelSmoother | Rauch-Tung-Striebel (RTS) smoother |
| RauchTungStriebelSmootherModel | RauchTungStriebelSmoother compatible model |
| Smoother | Abstract smoother |
| StandardMixturePdf | Mixture probability density with standard calculation of covariance |
| StochasticAdaptiveRungeKutta | Stochastic Adaptive Runge-Kutta method for solving a system of stochastic differential equations |
| StochasticDifferentialModel | StochasticAdaptiveRungeKutta compatible model |
| StochasticProcess | Abstract stochastic process |
| TwoFilterSmoother | Abstract smoother for estimating the state of a system by fusing forward and backward filtering passes |
| UniformPdf | Uniform distribution over a hyper-rectangle |
| UnscentedKalmanFilter | Unscented Kalman filter |
| UnscentedKalmanFilterMeasurementAdaptor | Adaptor mapping UnscentedTransformationModel interface to method calls in UnscentedKalmanFilterModel |
| UnscentedKalmanFilterModel | UnscentedKalmanFilter compatible model |
| UnscentedKalmanFilterTransitionAdaptor | Adaptor mapping UnscentedTransformationModel interface to method calls in UnscentedKalmanFilterModel |
| UnscentedKalmanSmoother | Unscented Kalman two-filter smoother |
| UnscentedKalmanSmootherBackwardTransitionAdaptor | Adaptor mapping UnscentedTransformationModel interface to method calls in UnscentedKalmanSmootherModel |
| UnscentedKalmanSmootherModel | UnscentedKalmanSmoother compatible model |
| UnscentedTransformation | Unscented transformation |
| UnscentedTransformationDefaults | Default parameter settings for UnscentedTransformation |
| UnscentedTransformationModel | UnscentedTransformation compatible model |
| VariancePartitioner | Partitions a set of weighted points into two sets at the mean of the dimension with greatest variance |
| WienerProcess | Multivariate Wiener process |
1.5.2