Generate R-many conditionally independent time series from the same AR(p) process

generate_AR() generates R-many conditionally independent time series from an AR(p) process using arima.sim().

Usage

generate_AR(phi, n, R = 1, burn = 50)

Arguments

phi

A vector containing the AR(p) coefficients. Same syntax used in arima.sim(), e.g. c(ar1coefficient, ar2coefficient).

n

A numeric vector that determines the length of the time series generated. Must contain R-many entries. Time series may be of different lengths.

R

An optional numeric scalar (default 1) that determines how many time series to generate. Each time series is stored column wise in output.

burn

An optional numeric scalar (default 50) that determines the n.start argument of the arima.sim() function.

Value

A list object that contains the R-long list object ts_list each containing a matrix of dimension (n[r] x 1) and the true_phi which is the user-specified phi.

Examples

## An AR(1) process with `phi = 0.5` and different length time-series
phi <- c(0.5)
R <- 5
n <- c(rep(2000, R - 2), rep(1000, R - 3))
burn <- 100
ts <- generate_AR(
  phi = c(0.5),
  n = n,
  R = R,
  burn = 100
)$ts_list
## `$ts_list` output generates an R-long list that each
## contains an (n[r] x 1) matrix

## Plot
## Create an empty plot
plot(
  x = c(),
  y = c(),
  xlim = c(0, 2000),
  ylim = range(ts),
  ylab = "",
  xlab = "time"
)
for (r in 1:3) {
  lines(ts[[r]][, 1], col = "blue")
}
for (r in 4:R) {
  lines(ts[[r]][, 1], col = "red")
}


#' ## An AR(1) process with `phi = 0.5` and same length time-series
phi <- c(0.5)
R <- 5
n <- rep(2000, R)
burn <- 100
ts <- generate_AR(
  phi = c(0.5),
  n = n,
  R = R,
  burn = 100
)$ts_list
## `$ts_list` output generates an R-long list that each
## contains an (n[r] x 1) matrix

## Plot
## Create an empty plot
plot(
  x = c(),
  y = c(),
  xlim = c(0, 2000),
  ylim = range(ts),
  ylab = "",
  xlab = "time"
)
for (r in 1:R) {
  lines(ts[[r]][, 1], col = "blue")
}