final MultivariateGaussian predictivePrior = particle.getLinearState().clone();
KalmanFilter kf = particle.getRegressionFilter(i);
final Matrix G = kf.getModel().getA();
predictivePrior.setMean(G.times(predictivePrior.getMean()));
predictivePrior.setCovariance(
G.times(predictivePrior.getCovariance()).times(G.transpose())
.plus(kf.getModelCovariance()));
// X * beta
final double lambda = Math.exp(data.getObservedData().times(
predictivePrior.getMean()).getElement(0));