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sample first= class=Point name=Unnamed dimension=3 values=[1.7164,-2.8773,-0.088868] last= class=Point name=Unnamed dimension=3 values=[-0.22779,-2.591,1.4601]
sample mean= class=Point name=Unnamed dimension=3 values=[0.4766,-0.53838,0.99785]
sample covariance= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[3.9398,2.8591,-0.016201,2.8591,8.9464,1.4878,-0.016201,1.4878,1.0051]
isoprobabilistic transformation= class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,x2,y0,y1,y2] evaluationImplementation=class=NatafEllipticalDistributionEvaluation mean=class=Point name=Unnamed dimension=3 values=[0.5,-0.5,1] inverseCholesky=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.5,-0.28868,0.20412,0,0.3849,-0.27217,0,0,1.2247] gradientImplementation=class=NatafEllipticalDistributionGradient inverseCholesky=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.5,-0.28868,0.20412,0,0.3849,-0.27217,0,0,1.2247] hessianImplementation=class=NatafEllipticalDistributionHessian
transformed sample first= class=Point name=Unnamed dimension=3 values=[0.6082,-1.2662,-0.43827] last= class=Point name=Unnamed dimension=3 values=[-0.3639,-0.59472,0.98404]
transformed sample mean= class=Point name=Unnamed dimension=3 values=[-0.0117,-0.0080179,0.0030405]
transformed sample covariance= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.98495,-0.018435,0.0031143,-0.018435,1.0184,-0.012994,0.0031143,-0.012994,1.0168]
inverse isoprobabilistic transformation= class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,x2,y0,y1,y2] evaluationImplementation=class=InverseNatafEllipticalDistributionEvaluation mean=class=Point name=Unnamed dimension=3 values=[0,0,0] cholesky=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[2,1.5,0,0,2.5981,0.57735,0,0,0.8165] gradientImplementation=class=InverseNatafEllipticalDistributionGradient cholesky=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[2,1.5,0,0,2.5981,0.57735,0,0,0.8165] hessianImplementation=class=InverseNatafEllipticalDistributionHessian
transformed back sample first= class=Point name=Unnamed dimension=3 values=[1.7164,-2.8773,-0.088868] last= class=Point name=Unnamed dimension=3 values=[-0.22779,-2.591,1.4601]
transformed back sample mean= class=Point name=Unnamed dimension=3 values=[0.4766,-0.53838,0.99785]
transformed back sample covariance= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[3.9398,2.8591,-0.016201,2.8591,8.9464,1.4878,-0.016201,1.4878,1.0051]
point= class=Point name=Unnamed dimension=3 values=[1,1,1]
transform value at point = class=Point name=Unnamed dimension=3 values=[0.25,0.43301,-0.30619]
transform gradient at point = class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.5,0,0,-0.28868,0.3849,0,0.20412,-0.27217,1.2247]
transform gradient at point (FD)= class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[0.5,0,0,-0.28868,0.3849,0,0.20412,-0.27217,1.2247]
transform hessian at point = class=SymmetricTensor implementation=class=TensorImplementation name=Unnamed rows=3 columns=3 sheets=3 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
transform hessian at point (FD) = class=SymmetricTensor implementation=class=TensorImplementation name=Unnamed rows=3 columns=3 sheets=3 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
inverse transform value at transformed point = class=Point name=Unnamed dimension=3 values=[1,1,1]
inverse transform gradient at transformed point (FD)= class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[2,0,0,1.5,2.5981,0,0,0.57735,0.8165]
inverse transform gradient at transformed point = class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[2,0,0,1.5,2.5981,0,0,0.57735,0.8165]
inverse transform hessian at transformed point = class=SymmetricTensor implementation=class=TensorImplementation name=Unnamed rows=3 columns=3 sheets=3 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
inverse transform hessian at transformed point (FD) = class=SymmetricTensor implementation=class=TensorImplementation name=Unnamed rows=3 columns=3 sheets=3 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
parameters gradient at point= class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=6 columns=3 values=[-0.5,0,0,-0.125,0,0,0.28868,-0.3849,0,0,-0.22222,0,-0.20412,0.27217,-1.2247,0,0,-0]
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