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polynomialFactory( Laplace = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Laplace name=Laplace dimension=1 lambda=1 mu=0 )
Laplace polynomial( 0 )= 1
Laplace polynomial( 1 )= 0.707107 * X
Laplace polynomial( 2 )= -0.447214 + 0.223607 * X^2
Laplace polynomial( 3 )= -0.57735 * X + 0.0481125 * X^3
Laplace polynomial( 4 )= 0.329734 - 0.25646 * X^2 + 0.00763274 * X^4
Laplace polynomial( 4 ) roots= [-5.67987,-1.15719,1.15719,5.67987]
Laplace polynomial( 4 ) nodes= [-5.67987,-1.15719,1.15719,5.67987] and weights= [0.0106869,0.489313,0.489313,0.0106869]
polynomialFactory( Logistic = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Logistic name=Logistic dimension=1 alpha=0 beta=1 )
Logistic polynomial( 0 )= 1
Logistic polynomial( 1 )= 0.551329 * X
Logistic polynomial( 2 )= -0.559017 + 0.169921 * X^2
Logistic polynomial( 3 )= -0.491265 * X + 0.035554 * X^3
Logistic polynomial( 4 )= 0.421875 - 0.205809 * X^2 + 0.00561421 * X^4
Logistic polynomial( 4 ) roots= [-5.87189,-1.47628,1.47628,5.87189]
Logistic polynomial( 4 ) nodes= [-5.87189,-1.47628,1.47628,5.87189] and weights= [0.0171899,0.48281,0.48281,0.0171899]
polynomialFactory( LogNormal = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=LogNormal name=LogNormal dimension=1 muLog=0 sigmaLog=1 gamma=0 )
LogNormal polynomial( 0 )= 1
LogNormal polynomial( 1 )= -0.762874 + 0.462706 * X
LogNormal polynomial( 2 )= 0.497602 - 0.41284 * X + 0.0247741 * X^2
LogNormal polynomial( 3 )= -0.309616 + 0.282291 * X - 0.0231719 * X^2 + 0.000171244 * X^3
LogNormal polynomial( 4 )= 0.189536 - 0.178532 * X + 0.0161047 * X^2 - 0.0001628 * X^3 + 1.57604e-07 * X^4
LogNormal polynomial( 4 ) roots= [1.18727,11.3306,96.7854,923.663]
LogNormal polynomial( 4 ) nodes= [1.18727,11.3306,96.7854,923.663] and weights= [0.954716,0.0452595,2.48459e-05,7.26933e-11]
polynomialFactory( Normal = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Normal name=Normal dimension=1 mean=class=NumericalPoint name=Unnamed dimension=1 values=[0] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] )
Normal polynomial( 0 )= 1
Normal polynomial( 1 )= X
Normal polynomial( 2 )= -0.707107 + 0.707107 * X^2
Normal polynomial( 3 )= -1.22474 * X + 0.408248 * X^3
Normal polynomial( 4 )= 0.612372 - 1.22474 * X^2 + 0.204124 * X^4
Normal polynomial( 4 ) roots= [-2.33441,-0.741964,0.741964,2.33441]
Normal polynomial( 4 ) nodes= [-2.33441,-0.741964,0.741964,2.33441] and weights= [0.0458759,0.454124,0.454124,0.0458759]
polynomialFactory( Rayleigh = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Rayleigh name=Rayleigh dimension=1 sigma=1 gamma=0 )
Rayleigh polynomial( 0 )= 1
Rayleigh polynomial( 1 )= -1.91306 + 1.5264 * X
Rayleigh polynomial( 2 )= 2.84565 - 5.00639 * X + 1.71446 * X^2
Rayleigh polynomial( 3 )= -3.78384 + 10.859 * X - 7.93394 * X^2 + 1.60694 * X^3
Rayleigh polynomial( 4 )= 4.72402 - 19.4426 * X + 22.5685 * X^2 - 9.59251 * X^3 + 1.32173 * X^4
Rayleigh polynomial( 4 ) roots= [0.396121,1.17673,2.20107,3.48361]
Rayleigh polynomial( 4 ) nodes= [0.396121,1.17673,2.20107,3.48361] and weights= [0.227998,0.538465,0.221578,0.0119592]
polynomialFactory( Student = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Student name=Student dimension=1 nu=22 mean=class=NumericalPoint name=Unnamed dimension=1 values=[0] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] )
Student polynomial( 0 )= 1
Student polynomial( 1 )= 0.953463 * X
Student polynomial( 2 )= -0.654654 + 0.59514 * X^2
Student polynomial( 3 )= -1.01929 * X + 0.277989 * X^3
Student polynomial( 4 )= 0.512989 - 0.839437 * X^2 + 0.10175 * X^4
Student polynomial( 4 ) roots= [-2.75415,-0.815266,0.815266,2.75415]
Student polynomial( 4 ) nodes= [-2.75415,-0.815266,0.815266,2.75415] and weights= [0.0314522,0.468548,0.468548,0.0314522]
polynomialFactory( Triangular = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Triangular name=Triangular dimension=1 a=-1 m=0.3 b=1 )
Triangular polynomial( 0 )= 1
Triangular polynomial( 1 )= -0.241355 + 2.41355 * X
Triangular polynomial( 2 )= -0.877334 - 0.428839 * X + 5.06542 * X^2
Triangular polynomial( 3 )= 0.259575 - 4.13679 * X - 1.01753 * X^2 + 10.3656 * X^3
Triangular polynomial( 4 )= 0.878133 + 0.925615 * X - 13.5192 * X^2 - 1.99648 * X^3 + 21.1809 * X^4
Triangular polynomial( 4 ) roots= [-0.742936,-0.235772,0.310364,0.762603]
Triangular polynomial( 4 ) nodes= [-0.742936,-0.235772,0.310364,0.762603] and weights= [0.0810886,0.334646,0.456437,0.127828]
polynomialFactory( Uniform = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Uniform name=Uniform dimension=1 a=-1 b=1 )
Uniform polynomial( 0 )= 1
Uniform polynomial( 1 )= 1.73205 * X
Uniform polynomial( 2 )= -1.11803 + 3.3541 * X^2
Uniform polynomial( 3 )= -3.96863 * X + 6.61438 * X^3
Uniform polynomial( 4 )= 1.125 - 11.25 * X^2 + 13.125 * X^4
Uniform polynomial( 4 ) roots= [-0.861136,-0.339981,0.339981,0.861136]
Uniform polynomial( 4 ) nodes= [-0.861136,-0.339981,0.339981,0.861136] and weights= [0.173927,0.326073,0.326073,0.173927]
polynomialFactory( Weibull = class=StandardDistributionPolynomialFactory orthonormalization algorithm=class=OrthonormalizationAlgorithm implementation=class=GramSchmidtAlgorithm measure=class=Weibull name=Weibull dimension=1 alpha=1 beta=3 gamma=0 )
Weibull polynomial( 0 )= 1
Weibull polynomial( 1 )= -2.75144 + 3.08119 * X
Weibull polynomial( 2 )= 5.3921 - 13.3967 * X + 7.27876 * X^2
Weibull polynomial( 3 )= -8.91794 + 36.5275 * X - 42.8504 * X^2 + 14.9827 * X^3
Weibull polynomial( 4 )= 13.3264 - 79.2309 * X + 149.529 * X^2 - 111.023 * X^3 + 28.1044 * X^4
Weibull polynomial( 4 ) roots= [0.315842,0.737023,1.19993,1.69759]
Weibull polynomial( 4 ) nodes= [0.315842,0.737023,1.19993,1.69759] and weights= [0.109605,0.491205,0.364361,0.03483]
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