demo/autoreg.R

In mpiktas/midasr: Mixed Data Sampling Regression

library(midasr)
theta_h0 <- function(p, dk) {
  i <- (1:dk - 1) / 100
  pol <- p[3] * i + p[4] * i^2
  (p[1] + p[2] * i) * exp(pol)
}

## Generate coefficients
theta0 <- theta_h0(c(-0.1, 10, -10, -10), 4 * 12)


xx <- ts(arima.sim(model = list(ar = 0.6), 3000 * 12), frequency = 12)

aa <- lapply(c(50, 100, 200, 500, 1000, 1500, 2000), function(n) {
  y <- midas_auto_sim(n, 0.5, xx, theta0, n_start = 200)
  x <- window(xx, start = start(y))
  midas_r(y ~ mls(y, 1, 1) + fmls(x, 4 * 12 - 1, 12, theta_h0), start = list(x = c(-0.1, 10, -10, -10)))
})

sapply(aa, function(x) c(nrow(x$model), coef(x)))

bb <- lapply(c(50, 100, 200, 500, 1000, 1500, 2000), function(n) {
  y <- midas_auto_sim(n, c(0.5, 0.1), xx, theta0, n_start = 200)
  x <- window(xx, start = start(y))
  midas_r(y ~ mls(y, 1:2, 1) + fmls(x, 4 * 12 - 1, 12, theta_h0), start = list(x = c(-0.1, 10, -10, -10)))
})

sapply(bb, function(x) c(nrow(x$model), coef(x)))