Man pages for nickpoison/nltsa
Nonlinear Time Series Analysis
| ARCH | Create an autoregressivemodel with ARCH(1) error |
| ARCH.optimal.logpdf | Log-likelihood of ARCH optimal kernel |
| ARCH.optimal.params | Parameters for ARCH optimal kernel |
| ARCH.optimal.rnd | Sample from ARCH optimal kernel |
| arp.mcmc | Normal AR(p) MCMC |
| bi.coh | Normalized Bispectrum |
| CPFSAEM | Run a Conditional Particle Stochastic Approximation EM chain |
| CPFSGgrowth | Run a Conditional Particle Stochastic Approximation SG chain |
| cpf.sisr | Conditional Particle filter via Sequential Importance... |
| CV | Coefficient of Variation of importance weights |
| EEG | EEG trace. |
| ESS | Effective Sample Size of importance weights |
| in.support.NoisyAR | Checks if parameters are valid for a Noisy AR model |
| loclike.logpdf | Log-pdf of the local likelihood of a Non linear state space... |
| loclike.logpdf.NoisyAR | Compute the local likelihood of a NoisyAR model |
| metronorm | Metropolis Normal |
| MH | Run a Metropolis-Hastings chain |
| MultinomialR | Multinomial resampling |
| nltsa-package | Nonlinear Time Series Analysis |
| NoisyAR | Create a Noisy Auto-Regressive(1) NLSS model |
| normalized.exponential | Normalized exponential of a vector |
| ParticleEM | Run a Particle EM chain |
| ParticleMarginalMH | Run a Particle Marginal Metropolis-Hastings chain |
| ParticleSAEM | Run a Particle Stochastic Approximation EM chain |
| ParticleSGGrowth | Run a Particle Stochastic Gradient for the Growth model |
| random.walk | Gaussian Random-walk proposal kernel |
| simulate.data | Simulation of a dataset for a NLSS |
| sis | Sequential Importance Sampling with Prior kernel for 1-D NLSS |
| siskernel | Sequential Importance Sampling with arbitrary kernel for 1-D... |
| sisr | Particle filter via Sequential Importance Sampling with... |
| sp500.gr | Growth Rate of the S&P 500 |
| Stovol | Create a Stochastic Volatility model |
