static GaussianProcessCovarianceOptimizationProblem() { // cumbersome initialization because of ConstrainedValueParameters maternIso1 = new CovarianceMaternIso(); SetConstrainedValueParameter(maternIso1.DParameter, 1); maternIso3 = new CovarianceMaternIso(); SetConstrainedValueParameter(maternIso3.DParameter, 3); maternIso5 = new CovarianceMaternIso(); SetConstrainedValueParameter(maternIso5.DParameter, 5); piecewisePoly0 = new CovariancePiecewisePolynomial(); SetConstrainedValueParameter(piecewisePoly0.VParameter, 0); piecewisePoly1 = new CovariancePiecewisePolynomial(); SetConstrainedValueParameter(piecewisePoly1.VParameter, 1); piecewisePoly2 = new CovariancePiecewisePolynomial(); SetConstrainedValueParameter(piecewisePoly2.VParameter, 2); piecewisePoly3 = new CovariancePiecewisePolynomial(); SetConstrainedValueParameter(piecewisePoly3.VParameter, 3); poly2 = new CovariancePolynomial(); poly2.DegreeParameter.Value.Value = 2; poly3 = new CovariancePolynomial(); poly3.DegreeParameter.Value.Value = 3; spectralMixture1 = new CovarianceSpectralMixture(); spectralMixture1.QParameter.Value.Value = 1; spectralMixture3 = new CovarianceSpectralMixture(); spectralMixture3.QParameter.Value.Value = 3; spectralMixture5 = new CovarianceSpectralMixture(); spectralMixture5.QParameter.Value.Value = 5; linear = new CovarianceLinear(); linearArd = new CovarianceLinearArd(); neuralNetwork = new CovarianceNeuralNetwork(); periodic = new CovariancePeriodic(); ratQuadraticArd = new CovarianceRationalQuadraticArd(); ratQuadraticIso = new CovarianceRationalQuadraticIso(); sqrExpArd = new CovarianceSquaredExponentialArd(); sqrExpIso = new CovarianceSquaredExponentialIso(); }
private CovarianceRationalQuadraticIso(CovarianceRationalQuadraticIso original, Cloner cloner) : base(original, cloner) { }
private CovarianceRationalQuadraticIso(CovarianceRationalQuadraticIso original, Cloner cloner) : base(original, cloner) { }