/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the mean is * <ul> * <li>if {@code df > 1} then {@code 0},</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalMean() { final double df = getDegreesOfFreedom(); if (df > 1) { return 0; } return Double.NaN; }
/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the variance is * <ul> * <li>if {@code df > 2} then {@code df / (df - 2)},</li> * <li>if {@code 1 < df <= 2} then positive infinity * ({@code Double.POSITIVE_INFINITY}),</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalVariance() { final double df = getDegreesOfFreedom(); if (df > 2) { return df / (df - 2); } if (df > 1 && df <= 2) { return Double.POSITIVE_INFINITY; } return Double.NaN; }
/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the mean is * <ul> * <li>if {@code df > 1} then {@code 0},</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalMean() { final double df = getDegreesOfFreedom(); if (df > 1) { return 0; } return Double.NaN; }
/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the mean is * <ul> * <li>if {@code df > 1} then {@code 0},</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalMean() { final double df = getDegreesOfFreedom(); if (df > 1) { return 0; } return Double.NaN; }
/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the variance is * <ul> * <li>if {@code df > 2} then {@code df / (df - 2)},</li> * <li>if {@code 1 < df <= 2} then positive infinity * ({@code Double.POSITIVE_INFINITY}),</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalVariance() { final double df = getDegreesOfFreedom(); if (df > 2) { return df / (df - 2); } if (df > 1 && df <= 2) { return Double.POSITIVE_INFINITY; } return Double.NaN; }
/** * {@inheritDoc} * * For degrees of freedom parameter {@code df}, the variance is * <ul> * <li>if {@code df > 2} then {@code df / (df - 2)},</li> * <li>if {@code 1 < df <= 2} then positive infinity * ({@code Double.POSITIVE_INFINITY}),</li> * <li>else undefined ({@code Double.NaN}).</li> * </ul> */ public double getNumericalVariance() { final double df = getDegreesOfFreedom(); if (df > 2) { return df / (df - 2); } if (df > 1 && df <= 2) { return Double.POSITIVE_INFINITY; } return Double.NaN; }
/** * @param param * degrees of freedom * @return T-distribution */ protected TDistribution getTDistribution(double param) { if (t == null || t.getDegreesOfFreedom() != param) { t = new TDistribution(param); } return t; }
TDistribution ta = (TDistribution) a; TDistribution tb = (TDistribution) b; return ta.getDegreesOfFreedom() == tb.getDegreesOfFreedom(); } else if (c == TriangularDistribution.class) { TriangularDistribution ta = (TriangularDistribution) a;
TDistribution ta = (TDistribution) a; TDistribution tb = (TDistribution) b; return ta.getDegreesOfFreedom() == tb.getDegreesOfFreedom(); } else if (c == TriangularDistribution.class) { TriangularDistribution ta = (TriangularDistribution) a;
} else if (c == TDistribution.class) { TDistribution td = (TDistribution) d; j.writeNumberField("dof", td.getDegreesOfFreedom()); } else if (c == TriangularDistribution.class) { TriangularDistribution td = (TriangularDistribution) d;
} else if (c == TDistribution.class) { TDistribution td = (TDistribution) d; j.writeNumberField("dof", td.getDegreesOfFreedom()); } else if (c == TriangularDistribution.class) { TriangularDistribution td = (TriangularDistribution) d;