C# Gaussian.IsProper方法代码示例

		public static Gaussian SampleAverageConditional(Gaussian sample, [SkipIfUniform] Gaussian mean, [Proper] Gamma variance)
		{
			if (variance.IsPointMass) return SampleAverageConditional(mean, variance.Point);
			if (mean.IsUniform()) return Gaussian.Uniform();
			double mx,vx,mm,vm;
			double a,b;
			sample.GetMeanAndVariance(out mx, out vx);
			mean.GetMeanAndVariance(out mm, out vm);
			a = variance.Shape;
			b = variance.Rate;
			if (sample.IsUniform()) return new Gaussian(mm, vm + a/b);
			double c = Math.Sqrt(2*b);
			double m = c*(mx-mm);
			double v = c*c*(vx+vm);
			double mu,vu;
			if(a < 1) throw new ArgumentException("variance.shape < 1");
			double m2p = m*m/v;
			if (false && Math.Abs(m*m/v) > 30) {
				double invV = 1/v;
				double invSqrtV = Math.Sqrt(invV);
				double mPlus = (m-v)*invSqrtV;
				double mMinus = (-m-v)*invSqrtV;
				double Zplus = MMath.NormalCdfRatio(mPlus);
				double Zminus = MMath.NormalCdfRatio(mMinus);
				double Z0 = Zminus + Zplus;
				double alpha = (Zminus - Zplus)/Z0;
				double beta = -(1 - 2/Z0*invSqrtV - alpha*alpha);
				alpha *= c;
				beta *= c*c;
				double weight = beta / (sample.Precision - beta);
				Gaussian result = new Gaussian();
				result.Precision = sample.Precision * weight;
				result.MeanTimesPrecision = weight * (sample.MeanTimesPrecision + alpha) + alpha;
				if (!result.IsProper()) throw new ImproperMessageException(result);
				if (double.IsNaN(result.Precision) || double.IsNaN(result.MeanTimesPrecision)) throw new ApplicationException("result is nan");
				return result;
			} else {
				//double logZ;
				//if(a == 1) LaplacianTimesGaussianMoments(m, v, out logZ, out mu, out vu);
				VarianceGammaTimesGaussianMoments5(a, m, v, out mu, out vu);
				//Console.WriteLine("mu = {0}, vu = {1}", mu, vu);
				//VarianceGammaTimesGaussianMoments(a, m, v, out mu, out vu);
				//Console.WriteLine("mu = {0}, vu = {1}", mu, vu);
				double r = vx/(vx+vm);
				double mp = r*(mu/c + mm) + (1-r)*mx;
				double vp = r*r*vu/(c*c) + r*vm;
				if (Double.IsNaN(vp)) throw new Exception("vp is NaN");
				Gaussian result = Gaussian.FromMeanAndVariance(mp, vp)/sample;
				if (!result.IsProper()) throw new ImproperMessageException(result);
				return result;
			}
		}