The last three decades have seen many developments towards the solutions of various problems of statistical inference concerning stochastic processes. The formulation of the inference procedures, when the sampled observations are no longer independent, and hence the classical Fisher-Neyrnan-Pearson-Wald theory does not apply, has been fOlli~dto be rather difficult. As a consequence large sample rules of procedures have been suggested and a parallel development in the probability limit theorems has made it possible to establish various useful asymptotic properties of these inference procedures with special applications to stationary stochastic processes.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:602430 |
| Date | January 1958 |
| Creators | Chanda, K. C. |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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