/** * Returns the interval for the given confidence value. * * @param conf the confidence value in the interval [0, 1] * @return the interval */ public double[][] predictIntervals(double conf) { updateModel(); return m_MixtureModel.predictIntervals(conf); }
/** * Returns textual description of this estimator. */ public String toString() { updateModel(); if (m_MixtureModel == null) { return ""; } return m_MixtureModel.toString(); }
/** * Returns the interval for the given confidence value. * * @param conf the confidence value in the interval [0, 1] * @return the interval */ public double[][] predictIntervals(double conf) { updateModel(); return m_MixtureModel.predictIntervals(conf); }
/** * Returns the quantile for the given percentage. * * @param percentage the percentage * @return the quantile */ public double predictQuantile(double percentage) { updateModel(); return m_MixtureModel.predictQuantile(percentage); }
/** * Returns the quantile for the given percentage. * * @param percentage the percentage * @return the quantile */ public double predictQuantile(double percentage) { updateModel(); return m_MixtureModel.predictQuantile(percentage); }
/** * Returns textual description of this estimator. */ public String toString() { updateModel(); if (m_MixtureModel == null) { return ""; } return m_MixtureModel.toString(); }
/** * Returns the natural logarithm of the density estimate at the given * point. * * @param value the value at which to evaluate * @return the natural logarithm of the density estimate at the given * value */ public double logDensity(double value) { updateModel(); if (m_MixtureModel == null) { return Math.log(Double.MIN_VALUE); } return m_MixtureModel.logDensity(value); }
/** * Returns the natural logarithm of the density estimate at the given * point. * * @param value the value at which to evaluate * @return the natural logarithm of the density estimate at the given * value */ public double logDensity(double value) { updateModel(); if (m_MixtureModel == null) { return Math.log(Double.MIN_VALUE); } return m_MixtureModel.logDensity(value); }