midas_mmm_sim {midasr}

Simulate MMM MIDAS regression model

Description

Simulate MMM MIDAS regression model

Usage

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

Value

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)