midas_si_sim: Simulate SI MIDAS regression model

In mpiktas/midasr: Mixed Data Sampling Regression

Simulate SI MIDAS regression model

Description

Simulate SI MIDAS regression model

Usage

midas_si_sim(
  n,
  m,
  theta,
  gfun,
  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
gfun	function, a function which takes a single index
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_si_sim(250,
  m = 12, theta = nnbeta(c(2, 4), 24),
  gfun = function(x) 0.03 * x^3,
  ar.x = 0.9, ar.y = 0.5, n.start = 100
)

mpiktas/midasr documentation built on Aug. 24, 2022, 2:32 p.m.