The cosine

The function provides a simple example of majorization, also used by Lange [2015]. We work out some additional details. Start with Since we see that provides a uniform quadratic majorizer. Thus the iteration map provides a uniform quadratic majorization algorithm.

Now and for we have and thus the algorithm converges to As Lange [2015] points out the algorithm has a cubic rate of convergence, because and thus As a consequence of cubic convergence, there is not much that can be done to improve the algorithm (which is of very limited practical usefulness anyway). Of course we could use the more precise majorizations but they mostly increase the amount of computation in an iteration and do not improve much. The quadratic majorization at has its minimum at 2.1974, the cubic majorization at 2.9952, and the quartic majorization at 2.9270. The three majorizations at are shown in Figure 1.

plot of chunk three

As a curiosity, we could also consider the sharp quadratic majorization which has support points at and Because of symmetry the correspondng majorization algorithm converges to in a single step in this case. In Figure 2 we show the uniform and sharp quadratic majorizations for .

plot of chunk cosine