R/RamdomARMod_linar2.R

In ChrisKust/rexpar: Simplicial Depth for Explosive Autoregressive Processes

RandomARMod_linar2 <- function(nobs, arp1, arp2, start = c(0, 0), cont = "0")
{
  y <- numeric(nobs)
  y[1] <- start[1]
  y[2] <- start[2]
  

 y <-  switch(cont,
      "0" = 
      {
        for(i in 3:length(y))
        {
          y[i] <- arp1 * y[i - 1] + arp2 * y[i - 2] + 0.1 * rnorm(1)
        }
        y
      },
      "1" =
      {
        u1 <- rnorm(nobs) * 0.1
        u2 <- (5 + rnorm(nobs) * 1)
        p1 <- rpois(nobs, 5 / 100)
        e <- u1 + p1 * u2
        for(i in 3:length(y))
        {
          y[i] <- arp1 * y[i - 1] + arp2 * y[i - 2] + e[i] - 0.007127848 
        }
        y
      },
      "2" =
      {
        alpha <- 10
        beta <- -3.665129
        u <- runif(nobs)
        e <- beta - alpha * log(( - log(u)))
        for(i in 3:length(y))
        {
          y[i] <- arp1 * y[i - 1] + arp2 * y[i - 2] + e[i]
        }
        y
      },
      "3" =
      {
        alpha <- 1.928
        beta <- -2
        gamma <- 10
        u <- runif(nobs)
        e <- beta + alpha * ( - log(u))^(- 1 / gamma)
        for(i in 3:length(y))
        {
          y[i] <- arp1 * y[i - 1] + arp2 * y[i - 2] + e[i]
        }
        y
      },
      "4" =
      {
        alpha <- 1
        beta <- 1
        e <- rgamma(nobs, alpha, beta) - 0.6932
        for(i in 3:length(y))
        {
          y[i] <- arp1 * y[i - 1] + arp2 * y[i - 2] + e[i]
        }
        y
      },
      stop("Insert a valid notion!")
  )
}