myDefautModel = class=ExponentialModel scale=class=Point name=Unnamed dimension=1 values=[1] amplitude=class=Point name=Unnamed dimension=1 values=[1] spatial correlation=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] isDiagonal=true
myModel = class=ExponentialModel scale=class=Point name=Unnamed dimension=1 values=[1] amplitude=class=Point name=Unnamed dimension=1 values=[2] spatial correlation=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] isDiagonal=true
covariance matrix at t = 1 : class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.47152]
covariance matrix at t = -1 : class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.47152]
covariance matrix at t = 4 : class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.0732626]
discretized covariance over the time grid=class=RegularGrid name=Unnamed start=0 step=0.333333 n=4 is
class=CovarianceMatrix dimension=4 implementation=class=MatrixImplementation name=Unnamed rows=4 columns=4 values=[4,2.86613,2.05367,1.47152,2.86613,4,2.86613,2.05367,2.05367,2.86613,4,2.86613,1.47152,2.05367,2.86613,4]
spatialCorrelation=class=CorrelationMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,1,0,1,1,0.5,0,0.5,1]
mySecondOrderModel = class= StationaryCovarianceModel
myHighModel = class=ExponentialModel scale=class=Point name=Unnamed dimension=1 values=[1] amplitude=class=Point name=Unnamed dimension=3 values=[1,1,1] spatial correlation=class=CorrelationMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,1,0,1,1,0.5,0,0.5,1] isDiagonal=false
covariance matrix at t = 1 : class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.367879,0.367879,0,0.367879,0.367879,0.18394,0,0.18394,0.367879]
covariance matrix at t = -1 : class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.367879,0.367879,0,0.367879,0.367879,0.18394,0,0.18394,0.367879]
covariance matrix at t = 4 : class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.0183156,0.0183156,0,0.0183156,0.0183156,0.00915782,0,0.00915782,0.0183156]
discretized covariance over the time grid=class=RegularGrid name=Unnamed start=0 step=0.333333 n=4 is
class=CovarianceMatrix dimension=12 implementation=class=MatrixImplementation name=Unnamed rows=12 columns=12 values=[1,1,0,0.716531,0.716531,0,0.513417,0.513417,0,0.367879,0.367879,0,1,1,0.5,0.716531,0.716531,0.358266,0.513417,0.513417,0.256709,0.367879,0.367879,0.18394,0,0.5,1,0,0.358266,0.716531,0,0.256709,0.513417,0,0.18394,0.367879,0.716531,0.716531,0,1,1,0,0.716531,0.716531,0,0.513417,0.513417,0,0.716531,0.716531,0.358266,1,1,0.5,0.716531,0.716531,0.358266,0.513417,0.513417,0.256709,0,0.358266,0.716531,0,0.5,1,0,0.358266,0.716531,0,0.256709,0.513417,0.513417,0.513417,0,0.716531,0.716531,0,1,1,0,0.716531,0.716531,0,0.513417,0.513417,0.256709,0.716531,0.716531,0.358266,1,1,0.5,0.716531,0.716531,0.358266,0,0.256709,0.513417,0,0.358266,0.716531,0,0.5,1,0,0.358266,0.716531,0.367879,0.367879,0,0.513417,0.513417,0,0.716531,0.716531,0,1,1,0,0.367879,0.367879,0.18394,0.513417,0.513417,0.256709,0.716531,0.716531,0.358266,1,1,0.5,0,0.18394,0.367879,0,0.256709,0.513417,0,0.358266,0.716531,0,0.5,1]
