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Simulate SI MIDAS regression model
midas_si_sim( n, m, theta, gfun, ar.x, ar.y, rand.gen = rnorm, n.start = NA, ... )
a list
number of observations to simulate.
integer, frequency ratio
vector, restriction coefficients for high frequency variable
function, a function which takes a single index
vector, AR parameters for simulating high frequency variable
vector, AR parameters for AR part of the model
function, a function for generating the regression innovations, default is rnorm
rnorm
integer, length of a 'burn-in' period. If NA, the default, a reasonable value is computed.
additional parameters to rand.gen
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 )
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