ts-models-tvARMA {forecastSNSTS} | R Documentation |
Returns a simulated time series Y_{1,T}, ..., Y_{T,T} that fulfills the following equation:
Y_{t,T} = ∑_{j=1}^p a_j(t/T) Y_{t-j,T} + σ(t/T) \varepsilon_{t} + ∑_{k=1}^q σ((t-k)/T) b_k(t/T) \varepsilon_{t-k},
where a_1, …, a_p, b_0, b_1, …, b_q are real-valued functions on [0,1], σ is a positive function on [0,1] and \varepsilon_t is white noise.
tvARMA(T = 128, a = list(), b = list(), sigma = function(u) { return(1) }, innov = function(n) { rnorm(n, 0, 1) })
T |
length of the time series to be returned |
a |
list of p real-valued functions defined on [0,1] |
b |
list of q real-valued functions defined on [0,1] |
sigma |
function |
innov |
a function with one argument |
Returns a tvARMA(p,q) time series with specified parameters.
## Taken from Section 6 in Dahlhaus (1997, AoS) a1 <- function(u) {1.8 * cos(1.5 - cos(4 * pi * u))} a2 <- function(u) {-0.81} plot(tvARMA(128, a = list(a1, a2), b = list()), type = "l")