generateData: Generates data from a linear Gaussian state space model

In pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings

Description

Generates data from a specific linear Gaussian state space model of the form x_{t} = φ x_{t-1} + σ_v v_t and y_t = x_t + σ_e e_t , where v_t and e_t denote independent standard Gaussian random variables, i.e. N(0,1).

Usage

generateData(theta, noObservations, initialState)

Arguments

theta	The parameters θ=\{φ,σ_v,σ_e\} of the LGSS model. The parameter φ that scales the current state in the state dynamics is restricted to [-1,1] to obtain a stable model. The standard deviations of the state process noise σ_v and the observation process noise σ_e must be positive.
noObservations	The number of time points to simulate.
initialState	The initial state.

Value

The function returns a list with the elements:

• x: The latent state for t=0,...,T.

• y: The observation for t=0,...,T.

Author(s)

Johan Dahlin [e-mail]

References

Dahlin, J. & Schon, T. B. "Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models." Journal of Statistical Software, Code Snippets, 88(2): 1–41, 2019.

pmhtutorial documentation built on May 2, 2019, 3:25 a.m.