Description Usage Arguments Details Value Author(s) Examples
View source: R/midas_r_methods.R
Extracts various coefficients of MIDAS regression
1 2 |
object |
|
midas |
logical, if |
term_names |
a character vector with term names. Default is |
... |
not used currently |
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.
a vector with coefficients
Vaidotas Zemlys
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | #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")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.