edu.jhu.hlt.util.stats.Stats Maven / Gradle / Ivy

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package edu.jhu.hlt.util.stats;

import org.apache.commons.math3.distribution.NormalDistribution;
import org.apache.commons.math3.linear.CholeskyDecomposition;
import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.random.Well44497b;

import edu.jhu.hlt.optimize.function.Function;
import edu.jhu.prim.util.random.Prng;
import edu.jhu.prim.vector.IntDoubleDenseVector;
import edu.jhu.prim.vector.IntDoubleVector;

/**
 * 
 * A collection of handy stats methods.
 * 
 * @author noandrews
 * 
 */
public class Stats {
	
	public static class SampleLikelihood {
		double [] theta;
		double value;
		public SampleLikelihood(double [] theta, double value) {
			this.theta = theta;
			this.value = value;
		}
	}
	
	/**
	 * @return	Vector of iid normally distributed random variables
	 */
	public static double [] getNormalVector(int D) {
	    RandomGenerator rng = new Well44497b(Prng.nextLong()); 
		double [] ret = new double[D];
		NormalDistribution N = new NormalDistribution(rng, 0, 1, 1e-6);
		for(int i=0; i hh) {
				return new SampleLikelihood(xx_prop.getColumnVector(0).toArray(), cur_lnpdf);
			}
			// Shrink slice to rejected point
			if(phi > 0) {
				phi_max = phi;
			} else if(phi < 0) {
				phi_min = phi;
			} else {
				throw new RuntimeException("Shrunk to current position and still not acceptable");
			}
			// Propose new angle difference
			phi = Prng.nextDouble()*(phi_max - phi_min) + phi_min;
		}
	}
	
}