overfit function produces an overfit table

overfit(xs, p = 24, type = "burg")

Arguments

xs	a time series
p	the order of overfitting (Default = 24)
type	the type of estimate to make, defaults to burg

Value

nothing, simply displays the factor table

Examples

test <- generate(aruma, 400, s = 4)
overfit(test,20)
#> 
#> Coefficients of Original polynomial:  
#> -0.0898 -0.0154 0.0125 0.9983 0.1263 0.0334 0.0498 0.0407 -0.0031 -0.0393 -0.1371 -0.0567 -0.0483 -0.0309 0.0686 0.0243 0.0108 0.0538 -0.0014 -0.0281 
#> 
#> Factor                 Roots                Abs Recip    System Freq 
#> 1+0.9978B             -1.0022               0.9978       0.5000
#> 1-0.0030B+0.9855B^2    0.0015+-1.0073i      0.9927       0.2498
#> 1-0.9917B              1.0084               0.9917       0.0000
#> 1-0.0179B+0.7603B^2    0.0118+-1.1468i      0.8719       0.2484
#> 1+0.7399B+0.7335B^2   -0.5043+-1.0531i      0.8565       0.3211
#> 1-1.1981B+0.7233B^2    0.8283+-0.8346i      0.8505       0.1256
#> 1+1.2622B+0.6511B^2   -0.9692+-0.7723i      0.8069       0.3929
#> 1-1.5600B+0.6400B^2    1.2187+-0.2778i      0.8000       0.0357
#> 1-0.6489B+0.6294B^2    0.5155+-1.1503i      0.7933       0.1829
#> 1+0.7529B             -1.3282               0.7529       0.5000
#> 1+1.3996B+0.5630B^2   -1.2429+-0.4809i      0.7503       0.4412
#> 1-0.6430B              1.5551               0.6430       0.0000
#>   
#>