I'm trying to learn how to use the dse-package. Doing a stabilitytest on a model.
I run the test on two models that are identical except for 

Model 1: TREND=0
Model 2: TREND=NULL

and find the following difference in output unexpected:

library(dse)
AR=array(c(1,-0.8,-0.15),c(3,1,1))
model=ARMA(A=AR,B=1,TREND=0)
stability(model)
#> Distinct roots of det(A(L)) and moduli are:
#>           [,1]      [,2]
#>[1,]  1.0000000 1.0000000
#>[2,]  1.0451762 1.0451762
#>[3,] -6.3785096 6.3785096
#>Trend not taken into account: The system is NOT stable.
#>[1] FALSE
#>attr(,"roots")
 #>    Inverse of distinct roots of det(A(L))    moduli
#>[1,]                              1.0000000 1.0000000
#>[2,]                              0.9567764 0.9567764
#>[3,]                             -0.1567764 0.1567764
#>Advarselsbesked:
#>In roots.ARMA(obj, fuzz = fuzz, randomize = FALSE) :
 #> Unit roots may need to be added for non-zero trend elements.

AR=array(c(1,-0.8,-0.15),c(3,1,1))
model=ARMA(A=AR,B=1,TREND=NULL)
stability(model)

#>Distinct roots of det(A(L)) and moduli are:
#>           [,1]      [,2]
#>[1,]  1.0451762 1.0451762
#>[2,] -6.3785096 6.3785096
#>The system is stable.
#>[1] TRUE
#>attr(,"roots")
#>     Inverse of distinct roots of det(A(L))    moduli
#>[1,]                              0.9567764 0.9567764
#>[2,]                             -0.1567764 0.1567764


I am using:
R version 3.0.3 (2014-03-06) "Warm Puppy"

Best Regards 
Jesper Hybel Pedersen
Denmark

 		 	   		  
	[[alternative HTML version deleted]]

