com.itemanalysis.psychometrics.polycor.PolychoricTwoStepOLD.java Source code

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Here is the source code for com.itemanalysis.psychometrics.polycor.PolychoricTwoStepOLD.java

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/*
 * Copyright 2012 J. Patrick Meyer
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.itemanalysis.psychometrics.polycor;

import org.apache.commons.math3.optimization.GoalType;
import org.apache.commons.math3.optimization.univariate.BrentOptimizer;
import org.apache.commons.math3.optimization.univariate.UnivariatePointValuePair;

import java.util.Formatter;

/**
 *
 * @author J. Patrick Meyer
 */
@Deprecated
public class PolychoricTwoStepOLD extends AbstractPolychoricCorrelationOLD {

    PolychoricLogLikelihoodTwoStep loglik = null;

    public PolychoricTwoStepOLD() {
        super();
    }

    /**
     * Compute the two-step approximation to the polychoric correlation.
     *
     * @param data two way array of frequency counts
     */
    public void compute(double[][] data) {
        loglik = new PolychoricLogLikelihoodTwoStep(data);
        BrentOptimizer brent = new BrentOptimizer(1e-10, 1e-14);
        UnivariatePointValuePair result = brent.optimize(200, loglik, GoalType.MINIMIZE, -1.0, 1.0);
        rhoComputed = true;
        rho = result.getPoint();
    }

    /**
     *
     * @return polychoric correlation
     */
    public double value() {
        return rho;
    }

    public double getCorrelationStandardError() {
        double[] x = { value() };
        return loglik.getStandardError(x);
    }

    /**
     *
     * @return row thresholds
     */
    public double[] getRowThresholds() {
        return loglik.getRowThresholds();
    }

    public double[] getValidRowThresholds() {
        return loglik.getValidRowThresholds();
    }

    /**
     *
     * @return column thresholds
     */
    public double[] getColumnThresholds() {
        return loglik.getColumnThresholds();
    }

    public double[] getValidColumnThresholds() {
        return loglik.getValidColumnThresholds();
    }

    public int getNumberOfValidRowThresholds() {
        return loglik.getNumberOfValidRowThresholds();
    }

    public int getNumberOfValidColumnThresholds() {
        return loglik.getNumberOfValidColumnThresholds();
    }

    /**
     * Returns an array of all parameters. This method is primarily
     * used to provide starting values for the maximum likelihood
     * method of computing the polychoric correlation.
     * 
     * @return
     */
    public double[] getParameterArray() {
        return loglik.getParameterArray(rho);
    }

    public String printVerbose() {
        double[] x = { rho };
        String s = loglik.print(x);
        return s;
    }

    public String printThresholds() {
        StringBuilder sb = new StringBuilder();
        Formatter f = new Formatter(sb);

        double r = this.value();
        double[] t = this.getRowThresholds();

        for (int i = 0; i < t.length - 1; i++) {
            f.format("% 6.4f", t[i]);
            f.format("%2s", "");
        }
        return f.toString();

    }

    public String print() {
        return "";
    }

}