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Simulation for Data Science with R by Matthias Templ

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Dealing with stochastic optimization

In difference to deterministic optimization, by using stochastic optimization one can find a different solution with the same starting values. This should also allow us to trap not (always) to a local optima.

Simplified procedures (Star Trek, Spaceballs, and Spaceballs princess)

As mentioned in the introduction of this chapter, in principle a (fine) grid, which should cover the whole distribution of f, can be used and evaluated for each grid point (Star Trek). Those grid coordinates having a maximum/minimum, provide an approximate solution of the optimization problem. Grid-based deterministic solutions to other problems are, for example, the Stahel-Donoho estimator for outlier detection (Stahel 1981a) (Stahel ...

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