R: Rcpp Bindings for Sequential Monte Carlo

# Rcpp Bindings for Sequential Monte Carlo

## Documentation for package ‘RcppSMC’ version 0.2.9

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

blockpfGaussianOpt | Block Sampling Particle Filter (Linear Gaussian Model; Optimal Proposal)
compareNCestimates | Conditional Sequential Monte Carlo Examples
kalmanFFBS | Conditional Sequential Monte Carlo Examples
LinReg | Simple Linear Regression
LinRegLA | Simple Linear Regression
LinRegLA_adapt | Simple Linear Regression
nonLinPMMH | Particle marginal Metropolis-Hastings for a non-linear state space model.
pfLineartBS | Particle Filter Example
pfLineartBSOnlinePlot | Particle Filter Example
pfNonlinBS | Nonlinear Bootstrap Particle Filter (Univariate Non-Linear State Space Model)
radiata | Radiata pine dataset (linear regression example)
RcppSMC.package.skeleton | Create a skeleton for a new package that intends to use RcpSMCp
simGaussian | Block Sampling Particle Filter (Linear Gaussian Model; Optimal Proposal)
simGaussianSSM | Conditional Sequential Monte Carlo Examples
simLineart | Particle Filter Example
simNonlin | Simulates from a simple nonlinear state space model.