midas_mmm_sim function

Simulate MMM MIDAS regression model

midas_mmm_sim(
  n,
  m,
  theta,
  intercept,
  pmmm,
  ar.x,
  ar.y,
  rand.gen = rnorm,
  n.start = NA,
  ...
)

Arguments

• n: number of observations to simulate.
• m: integer, frequency ratio
• theta: vector, restriction coefficients for high frequency variable
• intercept: vector of length 1, intercept for the model.
• pmmm: vector of length 2, slope for the MMM term and MMM parameter
• ar.x: vector, AR parameters for simulating high frequency variable
• ar.y: vector, AR parameters for AR part of the model
• rand.gen: function, a function for generating the regression innovations, default is rnorm
• n.start: integer, length of a 'burn-in' period. If NA, the default, a reasonable value is computed.
• ...: additional parameters to rand.gen

Returns

a list

Examples

nnbeta <- function(p, k) nbeta(c(1,p),k)

dgp <- midas_mmm_sim(250, m = 12, theta = nnbeta(c(2, 4), 24), 
                           intercept = c(1), pmmm = c(1.5, 1), 
                           ar.x = 0.9, ar.y = 0.5, n.start = 100)
z <- cbind(1, mls(dgp$y, 1:2, 1))
colnames(z) <- c("Intercept", "y1", "y2")
X <- mls(dgp$x, 0:23, 12)

mmm_mod <- midas_mmm_plain(dgp$y, X, z, nnbeta, 
                          start_mmm = c(1.5, 1), 
                          start_x = c(2, 4), start_z=c(1, 0.5, 0)) 

coef(mmm_mod)