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oai:www.ideals.illinois.edu:2142/83015 2023-07-11 col_2142_5131 col_2142_13851 com_2142_5130 com_2142_684 com_2142_397

Leuthold, Raymond M. Wei, Anning 2015-09-25T20:55:49Z 2015-09-25T20:55:49Z 10000-01-01 1997 1997 This study has advanced the research methods and procedures of nonlinear dynamics modeling. Some basic properties of ARCH processes have been highlighted since they were not given enough attention in the past and lead to the misuse of the ARCH model. The study has introduced the long memory model, especially the AFIMA model, to agricultural market study for the first time. The study suggests that various linear and nonlinear filters should be used carefully in chaos study since it has been found that they can distort potential chaotic structures in the data. The typical chaos analysis must start with constructing the phase space, and the parameters of phase should be specified carefully. Made available in DSpace on 2015-09-25T20:55:49Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 9717344.pdf: 5417984 bytes, checksum: 8fbd0f3c0642e0e1cfaa3783dc24ce41 (MD5) Previous issue date: 1997 Embargo set by: Seth Robbins for item 84296 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 151 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997. http://hdl.handle.net/2142/83015 (MiAaPQ)AAI9717344 eng Economics, Finance Long Agricultural Futures Price Series: ARCH, Long Memory, or Chaos Processes text Agricultural Economics Agricultural Economics University of Illinois at Urbana-Champaign Dissertation Ph.D.