# summary.FCVAR_roots: Print Summary of Roots of the Characteristic Polynomial In FCVAR: Estimation and Inference for the Fractionally Cointegrated VAR

 summary.FCVAR_roots R Documentation

## Print Summary of Roots of the Characteristic Polynomial

### Description

`summary.FCVAR_roots` prints the output of `GetCharPolyRoots` to screen. `GetCharPolyRoots` calculates the roots of the characteristic polynomial to plot them with the unit circle transformed for the fractional model, see Johansen (2008).

### Usage

```## S3 method for class 'FCVAR_roots'
summary(object, ...)
```

### Arguments

 `object` An S3 object of type `FCVAR_roots` with the following elements: `cPolyRoots`A vector of the roots of the characteristic polynomial. It is an element of the list of estimation `results` output from `FCVARestn`. `b`A numeric value of the fractional cointegration parameter. `...` additional arguments affecting the summary produced.

### Note

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

### References

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

`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()`, `plot.FCVAR_roots()`, `summary.MVWN_stats()`

### Examples

```
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.