midas_lstr_sim function

Simulate LSTR MIDAS regression model

midas_lstr_sim(
  n,
  m,
  theta,
  intercept,
  plstr,
  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.
• plstr: vector of length 4, slope for the LSTR term and LSTR parameters
• 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_lstr_sim(250, m = 12, theta = nnbeta(c(2, 4), 24), 
                           intercept = c(1), plstr = c(1.5, 1, log(1), 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)

lstr_mod <- midas_lstr_plain(dgp$y, X, z, nnbeta, 
                          start_lstr = c(1.5, 1, 1, 1), 
                          start_x = c(2, 4), start_z=c(1, 0.5, 0)) 

coef(lstr_mod)