/**
* Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.financial.timeseries.analysis;
import org.apache.commons.lang.Validate;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.opengamma.analytics.math.function.Function1D;
import com.opengamma.analytics.math.statistics.distribution.ChiSquareDistribution;
import com.opengamma.timeseries.DoubleTimeSeries;
import com.opengamma.util.ArgumentChecker;
/**
*
*/
public class LiMcLeodPortmanteauIIDHypothesis extends IIDHypothesis {
private static final Logger s_logger = LoggerFactory.getLogger(LiMcLeodPortmanteauIIDHypothesis.class);
private final Function1D<DoubleTimeSeries<?>, double[]> _calculator = new AutocorrelationFunctionCalculator();
private final double _criticalValue;
private final int _h;
public LiMcLeodPortmanteauIIDHypothesis(final double level, final int maxLag) {
if (!ArgumentChecker.isInRangeExcludingLow(0, 1, level)) {
throw new IllegalArgumentException("Level must be between 0 and 1");
}
if (maxLag == 0) {
throw new IllegalArgumentException("Lag cannot be zero");
}
if (maxLag < 0) {
s_logger.info("Lag was negative; using absolute value");
}
_h = Math.abs(maxLag);
_criticalValue = new ChiSquareDistribution(_h).getInverseCDF(1 - level);
}
@Override
public boolean testIID(final DoubleTimeSeries<?> x) {
Validate.notNull(x, "x");
if (x.size() < _h) {
throw new IllegalArgumentException("Time series must have at least " + _h + " points");
}
final DoubleTimeSeries<?> tsSq = x.multiply(x);
final double[] autocorrelation = _calculator.evaluate(tsSq);
double q = 0;
final int n = x.size();
for (int i = 1; i < _h; i++) {
q += autocorrelation[i] * autocorrelation[i] / (n - i);
}
q *= n * (n + 2);
return q < _criticalValue;
}
}