plot.FCVAR_roots: Plot Roots of the Characteristic Polynomial

View source: R/FCVAR_post.R

plot.FCVAR_rootsR Documentation

Plot Roots of the Characteristic Polynomial


plot.FCVAR_roots plots the output of GetCharPolyRoots to screen or to a file. GetCharPolyRoots calculates the roots of the characteristic polynomial and plots them with the unit circle transformed for the fractional model, see Johansen (2008).


## S3 method for class 'FCVAR_roots'
plot(x, y = NULL, ...)



An S3 object of type FCVAR_roots with the following elements: #'


A vector of the roots of the characteristic polynomial. It is an element of the list of estimation results output from FCVARestn.


A numeric value of the fractional cointegration parameter.


An argument for generic method plot that is not used in plot.FCVAR_roots.


Arguments to be passed to methods, such as graphical parameters for the generic plot function.


The roots are calculated from the companion form of the VAR, where the roots are given as the inverse eigenvalues of the coefficient matrix.


Johansen, S. (2008). "A representation theory for a class of vector autoregressive models for fractional processes," Econometric Theory 24, 651-676.

See Also

FCVARoptions to set default estimation options. FCVARestn to estimate the model for which to calculate the roots of the characteristic polynomial. summary.FCVAR_roots prints the output of GetCharPolyRoots to screen.

Other FCVAR postestimation functions: FCVARboot(), FCVARhypoTest(), GetCharPolyRoots(), MVWNtest(), summary.FCVAR_roots(), summary.MVWN_stats()


opt <- FCVARoptions()
opt$gridSearch   <- 0 # Disable grid search in optimization.
opt$dbMin        <- c(0.01, 0.01) # Set lower bound for d,b.
opt$dbMax        <- c(2.00, 2.00) # Set upper bound for d,b.
opt$constrained  <- 0 # Impose restriction dbMax >= d >= b >= dbMin ? 1 <- yes, 0 <- no.
x <- votingJNP2014[, c("lib", "ir_can", "un_can")]
results <- FCVARestn(x, k = 2, r = 1, opt)
FCVAR_CharPoly <- GetCharPolyRoots(results$coeffs, opt, k = 2, r = 1, p = 3)
summary(object = FCVAR_CharPoly)
graphics::plot(x = FCVAR_CharPoly)

FCVAR documentation built on May 5, 2022, 9:06 a.m.