Extracts various coefficients of MIDAS regression
# S3 method for midas_r
coef(object, midas = FALSE, term_names = NULL, ...)
a vector with coefficients
midas_r
object
logical, if TRUE
, MIDAS coefficients are returned, if FALSE
(default), coefficients of NLS problem are returned
a character vector with term names. Default is NULL
, which means that coefficients of all the terms are returned
not used currently
Vaidotas Zemlys
MIDAS regression has two sets of cofficients. The first set is the coefficients associated with the parameters of weight functions associated with MIDAS regression terms. These are the coefficients of the NLS problem associated with MIDAS regression. The second is the coefficients of the linear model, i.e the values of weight functions of terms, or so called MIDAS coefficients. By default the function returns the first set of the coefficients.
#Simulate MIDAS regression
n<-250
trend<-c(1:n)
x<-rnorm(4*n)
z<-rnorm(12*n)
fn.x <- nealmon(p=c(1,-0.5),d=8)
fn.z <- nealmon(p=c(2,0.5,-0.1),d=17)
y<-2+0.1*trend+mls(x,0:7,4)%*%fn.x+mls(z,0:16,12)%*%fn.z+rnorm(n)
eqr<-midas_r(y ~ trend + mls(x, 0:7, 4, nealmon) +
mls(z, 0:16, 12, nealmon),
start = list(x = c(1, -0.5), z = c(2, 0.5, -0.1)))
coef(eqr)
coef(eqr, term_names = "x")
coef(eqr, midas = TRUE)
coef(eqr, midas = TRUE, term_names = "x")
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