myAntecedentProcess =   ARMA process dimension = 1
X_{0,t} = E_{0,t}
with E_t ~ Normal(mu = 0, sigma = 1)
myCompositeProcess =  class=CompositeProcess function=class=FieldFunction name=Unnamed implementation=class=ValueFunction evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[2 * x + 5.0] antecedent=class= ARMA timeGrid=class=RegularGrid name=Unnamed start=0 step=0.1 n=11 coefficients AR=class=ARMACoefficients coefficients MA=class=ARMACoefficients noiseDistribution= class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] state= class= ARMAState x= class=Sample name=Unnamed description=[] implementation=class=SampleImplementation name=Unnamed size=0 dimension=1 data=[] epsilon= class=Sample name=Unnamed description=[] implementation=class=SampleImplementation name=Unnamed size=0 dimension=1 data=[]
One realization= 
     [          y0       ]
 0 : [ 0        0.63723  ]
 1 : [ 0.1      5.70008  ]
 2 : [ 0.2      4.28999  ]
 3 : [ 0.3      7.8745   ]
 4 : [ 0.4      6.62134  ]
 5 : [ 0.5      6.58631  ]
 6 : [ 0.6      4.05895  ]
 7 : [ 0.7      5.52204  ]
 8 : [ 0.8      0.419876 ]
 9 : [ 0.9      2.43423  ]
10 : [ 1        2.37644  ]
