ou2 {pomp} | R Documentation |
ou2()
constructs a ‘pomp’ object encoding a bivariate discrete-time Ornstein-Uhlenbeck process with noisy observations.
ou2(alpha_1 = 0.8, alpha_2 = -0.5, alpha_3 = 0.3, alpha_4 = 0.9, sigma_1 = 3, sigma_2 = -0.5, sigma_3 = 2, tau = 1, x1_0 = -3, x2_0 = 4, times = 1:100, t0 = 0)
alpha_1, alpha_2, alpha_3, alpha_4 |
entries of the alpha matrix, in column-major order.
That is, |
sigma_1, sigma_2, sigma_3 |
entries of the lower-triangular sigma matrix.
|
tau |
measurement error s.d. |
x1_0, x2_0 |
latent variable values at time |
times |
vector of observation times |
t0 |
the zero time |
If the state process is X(t) = (x_{1}(t),x_{2}(t)), then
X(t+1) = α X(t) + σ ε(t),
where α and σ are 2x2 matrices, σ is lower-triangular, and ε(t) is standard bivariate normal. The observation process is Y(t) = (y_1(t),y_2(t)), where y_i(t) \sim \mathrm{normal}(x_i(t),τ).
A ‘pomp’ object with simulated data.
Other pomp examples: blowflies
,
dacca
, ebola
,
gompertz
, measles
,
ricker
, rw2
,
sir_models
, verhulst
po <- ou2() plot(po) coef(po) x <- simulate(po) plot(x) pf <- pfilter(po,Np=1000) logLik(pf)