REPRODUCING KERNELS IN PROBABILITY AND STATISTICS
Since the first works laying its foundations as a subfield of Complex Analysis, the theory of reproducing kernels has proved to be a powerful tool in many fields of Pure and Applied Mathematics. The aim of this paper is to give some idea of how and why this theory interacts with Probability and Statistics.
- Reproducing kernels
- positive type functions
- stochastic processes
- non-parametic estimation
- random measures
- law of iterated logarithm