Example usage for org.apache.commons.math3.exception.util LocalizedFormats ARRAY_SIZE_EXCEEDS_MAX_VARIABLES

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Prototype

LocalizedFormats ARRAY_SIZE_EXCEEDS_MAX_VARIABLES

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Usage

From source file:experiment.SimpleRegression_bug.java

/**
 * Performs a regression on data present in buffers including only regressors
 * indexed in variablesToInclude and outputs a RegressionResults object
 * @param variablesToInclude an array of indices of regressors to include
 * @return RegressionResults acts as a container of regression output
 * @throws MathIllegalArgumentException if the variablesToInclude array is null or zero length
 * @throws OutOfRangeException if a requested variable is not present in model
 *///from ww  w .j a v a  2  s.  c om
public RegressionResults regress(int[] variablesToInclude) throws MathIllegalArgumentException {
    if (variablesToInclude == null || variablesToInclude.length == 0) {
        throw new MathIllegalArgumentException(LocalizedFormats.ARRAY_ZERO_LENGTH_OR_NULL_NOT_ALLOWED);
    }
    if (variablesToInclude.length > 2 || (variablesToInclude.length > 1 && !hasIntercept)) {
        throw new ModelSpecificationException(LocalizedFormats.ARRAY_SIZE_EXCEEDS_MAX_VARIABLES,
                (variablesToInclude.length > 1 && !hasIntercept) ? 1 : 2);
    }

    if (hasIntercept) {
        if (variablesToInclude.length == 2) {
            if (variablesToInclude[0] == 1) {
                throw new ModelSpecificationException(LocalizedFormats.NOT_INCREASING_SEQUENCE);
            } else if (variablesToInclude[0] != 0) {
                throw new OutOfRangeException(variablesToInclude[0], 0, 1);
            }
            if (variablesToInclude[1] != 1) {
                throw new OutOfRangeException(variablesToInclude[0], 0, 1);
            }
            return regress();
        } else {
            if (variablesToInclude[0] != 1 && variablesToInclude[0] != 0) {
                throw new OutOfRangeException(variablesToInclude[0], 0, 1);
            }
            final double _mean = sumY * sumY / n;
            final double _syy = sumYY + _mean;
            if (variablesToInclude[0] == 0) {
                //just the mean
                final double[] vcv = new double[] { sumYY / (((n - 1) * n)) };
                final double[] params = new double[] { ybar };
                return new RegressionResults(params, new double[][] { vcv }, true, n, 1, sumY, _syy + _mean,
                        sumYY, true, false);

            } else if (variablesToInclude[0] == 1) {
                //final double _syy = sumYY + sumY * sumY / ((double) n);
                final double _sxx = sumXX + sumX * sumX / n;
                final double _sxy = sumXY + sumX * sumY / n;
                final double _sse = FastMath.max(0d, _syy - _sxy * _sxy / _sxx);
                final double _mse = _sse / ((n - 1));
                if (!Double.isNaN(_sxx)) {
                    final double[] vcv = new double[] { _mse / _sxx };
                    final double[] params = new double[] { _sxy / _sxx };
                    return new RegressionResults(params, new double[][] { vcv }, true, n, 1, sumY, _syy, _sse,
                            false, false);
                } else {
                    final double[] vcv = new double[] { Double.NaN };
                    final double[] params = new double[] { Double.NaN };
                    return new RegressionResults(params, new double[][] { vcv }, true, n, 1, Double.NaN,
                            Double.NaN, Double.NaN, false, false);
                }
            }
        }
    } else {
        if (variablesToInclude[0] != 0) {
            throw new OutOfRangeException(variablesToInclude[0], 0, 0);
        }
        return regress();
    }

    return null;
}

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