本文整理汇总了Java中cern.jet.random.engine.MersenneTwister.DEFAULT_SEED属性的典型用法代码示例。如果您正苦于以下问题：Java MersenneTwister.DEFAULT_SEED属性的具体用法？Java MersenneTwister.DEFAULT_SEED怎么用？Java MersenneTwister.DEFAULT_SEED使用的例子？那么, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类cern.jet.random.engine.MersenneTwister的用法示例。
在下文中一共展示了MersenneTwister.DEFAULT_SEED属性的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testFlat
@Test
//TODO if this interpolator cannot get the answer right then an exception should be thrown
public void testFlat() {
final RandomEngine random = new MersenneTwister64(MersenneTwister.DEFAULT_SEED);
final double x1 = 10 * random.nextDouble();
final double x2 = 10 * random.nextDouble();
final double x3 = 10 * random.nextDouble();
// Fails utterly for flat surface since the variogram function will be zero for all r
final InterpolatorND interpolator = new KrigingInterpolatorND(1.99);
final InterpolatorNDDataBundle dataBundle = interpolator.getDataBundle(FLAT_DATA);
assertEquals(INTERPOLATOR.interpolate(dataBundle, new double[] {x1, x2, x3}), 0, 0);
}
示例2: test
@Test
public void test() {
final double mu = 0.367;
final double b = 1.4;
final ProbabilityDistribution<Double> distribution = new LaplaceDistribution(mu, b, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final int n = 500000;
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = distribution.nextRandom();
}
final LaplaceDistribution result = (LaplaceDistribution) ESTIMATOR.evaluate(x);
final double eps = 1e-2;
assertEquals(1, result.getB() / b, eps);
assertEquals(1, result.getMu() / mu, eps);
}
开发者ID:DevStreet，项目名称:FinanceAnalytics，代码行数:15，代码来源:LaplaceDistributionMaximumLikelihoodEstimatorTest.java
示例3: test
@Test
public void test() {
final int n = 500000;
final double k = 1.34;
final ProbabilityDistribution<Double> p1 = new ChiSquareDistribution(k, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final ChiSquareDistribution p2 = (ChiSquareDistribution) CALCULATOR.evaluate(x);
assertEquals(p2.getDegreesOfFreedom(), k, 2.5e-2);
}
示例4: test
@Test
public void test() {
final int n = 500000;
final double k = 0.97;
final double theta = 0.46;
final ProbabilityDistribution<Double> p1 = new GammaDistribution(k, theta, new MersenneTwister(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final GammaDistribution p2 = (GammaDistribution) CALCULATOR.evaluate(x);
final double eps = 0.025;
assertEquals(p2.getK(), k, eps);
assertEquals(p2.getTheta(), theta, eps);
}
示例5: test
@Test
public void test() {
final int n = 500000;
final double mu = 4.5;
final double sigma = 0.86;
final ProbabilityDistribution<Double> p1 = new NormalDistribution(mu, sigma, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final NormalDistribution p2 = (NormalDistribution) CALCULATOR.evaluate(x);
assertEquals(p2.getMean(), mu, 2.5e-2);
assertEquals(p2.getStandardDeviation(), sigma, 2.5e-2);
}
示例6: test
@Test(groups = TestGroup.UNIT_SLOW)
public void test() {
final int n = 500000;
final double eps = 5e-2;
final double nu = 5.4;
final ProbabilityDistribution<Double> p1 = new StudentTDistribution(nu, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final StudentTDistribution p2 = (StudentTDistribution) ESTIMATOR.evaluate(x);
assertEquals(p2.getDegreesOfFreedom(), nu, eps);
}
开发者ID:DevStreet，项目名称:FinanceAnalytics，代码行数:13，代码来源:StudentTDistributionMaximumLikelihoodEstimatorTest.java
示例7: test
@Test
public void test() {
final int n = 500000;
final double eps = 1e-2;
final double mu = -1.3;
final double sigma = 0.4;
final ProbabilityDistribution<Double> p1 = new NormalDistribution(mu, sigma, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final NormalDistribution p2 = (NormalDistribution) ESTIMATOR.evaluate(x);
assertEquals(p2.getMean(), mu, eps);
assertEquals(p2.getStandardDeviation(), sigma, eps);
}
开发者ID:DevStreet，项目名称:FinanceAnalytics，代码行数:15，代码来源:NormalDistributionMaximumLikelihoodEstimatorTest.java
示例8: SmileInterpolator
public SmileInterpolator(final VolatilityFunctionProvider<T> model) {
this(MersenneTwister.DEFAULT_SEED, model);
}
示例9: MarkovChain
public MarkovChain(final double vol1, final double vol2, final double lambda12, final double lambda21, final double probState1) {
this(vol1, vol2, lambda12, lambda21, probState1, MersenneTwister.DEFAULT_SEED);
}