We present a preliminary test for nonlinear structure in large data sets. This procedure consists of transforming the data to remove the correlations, then discretizing the data and finally, studying the cell counts in the resulting contingency table. Formal tests can be performed using the usual chi-squared test statistic; there are several forms of this test depending on the transformations and the discretizing schemes. We derive the limiting joint distribution of the cell counts and the limiting distribution of the chi-squared statistic in various situations, and derive the exact first two moments of the chi-squared test statistic in one situation. We also present simulation results for the limiting distribution of the chi-squared statistic via quantile-quantile plots and then present several examples from both simulated and real data sets. / Source: Dissertation Abstracts International, Volume: 53-10, Section: B, page: 5282. / Major Professor: Fred Huffer. / Thesis (Ph.D.)--The Florida State University, 1992.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76782 |
| Contributors | Park, Cheolyong., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 86 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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