Loading…
An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables
In this study analysis of data whose character was kept secret was performed by employing a variety of nonlinear approaches. The idea was to test the ability of approaches stemming from the theory of nonlinear dynamical systems to infer the true properties hidden in the data. The approaches employed...
Saved in:
| Published in: | Bulletin of the American Meteorological Society 1994-09, Vol.75 (9), p.1623-1633 |
|---|---|
| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | |
| container_end_page | 1633 |
| container_issue | 9 |
| container_start_page | 1623 |
| container_title | Bulletin of the American Meteorological Society |
| container_volume | 75 |
| creator | Tsonis, A. A. Triantafyllou, G. N. Elsner, J. B. Holdzkom, J. J. Kirwan, A. D. |
| description | In this study analysis of data whose character was kept secret was performed by employing a variety of nonlinear approaches. The idea was to test the ability of approaches stemming from the theory of nonlinear dynamical systems to infer the true properties hidden in the data. The approaches employed include dimension estimation, nonlinear prediction, Lyapunov exponent estimation, and false nearest neighbors. It is concluded that even though the methods have problems and occasionally may be inconclusive, when correctly applied they are effective in delineating the dynamics underlying the data. |
| doi_str_mv | 10.1175/1520-0477(1994)075<1623:AIOTAO>2.0.CO;2 |
| format | article |
| fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_18189636</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>26231966</jstor_id><sourcerecordid>26231966</sourcerecordid><originalsourceid>FETCH-LOGICAL-c353t-ca6018fa23b4d5860b7869a032b7078d9b8afd7a3b81ffa0f025c5eaeea862e23</originalsourceid><addsrcrecordid>eNqFkd9rFDEQx4MoeLb9E4QgIvqw10mymx8qwnLa9qC6LxUfQ3YvsTn2kprsFe6_N8uVe_DFlwyT-eQ7mfkidElgSYhoLklDoYJaiPdEqfoDiOYz4ZR9bNfdXdt9oUtYrrpP9BlanMjnaAEArCqHeIle5bydUybJAv1qA16HR5sn_9tMPgYcHZ7uLW57P_rpMKc_Yhh9sCbh73a6j5uMp1geOZvw10MwOz9k7FLc4a7PNj2afrT5HL1wZsz24imeoZ9X3-5WN9Vtd71etbfVwBo2VYPhQKQzlPX1ppEceiG5MsBoL0DIjeqlcRthWC-JcwYc0GZorLHWSE4tZWfo3VH3IcU_-zKG3vk82HE0wcZ91kQSqTjjBXzzD7iN-xTK3zRllDOllPg_JEEW6PoIDSnmnKzTD8nvTDpoAnq2SM-L1_Pi9WyRhvmqWKSPFmmqQa9KKEpvn9qZPJjRJRMGn09yNeU1kBl7fcS2eYrpVKZFkijO2V9OFJzW</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>232639997</pqid></control><display><type>article</type><title>An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables</title><source>JSTOR Archival Journals and Primary Sources Collection</source><creator>Tsonis, A. A. ; Triantafyllou, G. N. ; Elsner, J. B. ; Holdzkom, J. J. ; Kirwan, A. D.</creator><creatorcontrib>Tsonis, A. A. ; Triantafyllou, G. N. ; Elsner, J. B. ; Holdzkom, J. J. ; Kirwan, A. D.</creatorcontrib><description>In this study analysis of data whose character was kept secret was performed by employing a variety of nonlinear approaches. The idea was to test the ability of approaches stemming from the theory of nonlinear dynamical systems to infer the true properties hidden in the data. The approaches employed include dimension estimation, nonlinear prediction, Lyapunov exponent estimation, and false nearest neighbors. It is concluded that even though the methods have problems and occasionally may be inconclusive, when correctly applied they are effective in delineating the dynamics underlying the data.</description><identifier>ISSN: 0003-0007</identifier><identifier>EISSN: 1520-0477</identifier><identifier>DOI: 10.1175/1520-0477(1994)075<1623:AIOTAO>2.0.CO;2</identifier><identifier>CODEN: BAMOAD</identifier><language>eng</language><publisher>Boston, MA: American Meteorological Society</publisher><subject>Autocorrelation ; Chaos theory ; Dynamical systems ; Earth, ocean, space ; Exact sciences and technology ; External geophysics ; Geophysics. Techniques, methods, instrumentation and models ; Meteorology ; Neighborhoods ; Series convergence ; Spectral index ; Time series ; Time series forecasting ; Time series models</subject><ispartof>Bulletin of the American Meteorological Society, 1994-09, Vol.75 (9), p.1623-1633</ispartof><rights>Copyright 1994, American Meteorological Society (AMS)</rights><rights>1994 INIST-CNRS</rights><rights>Copyright American Meteorological Society Sep 1994</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26231966$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26231966$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,58238,58471</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=4264012$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Tsonis, A. A.</creatorcontrib><creatorcontrib>Triantafyllou, G. N.</creatorcontrib><creatorcontrib>Elsner, J. B.</creatorcontrib><creatorcontrib>Holdzkom, J. J.</creatorcontrib><creatorcontrib>Kirwan, A. D.</creatorcontrib><title>An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables</title><title>Bulletin of the American Meteorological Society</title><description>In this study analysis of data whose character was kept secret was performed by employing a variety of nonlinear approaches. The idea was to test the ability of approaches stemming from the theory of nonlinear dynamical systems to infer the true properties hidden in the data. The approaches employed include dimension estimation, nonlinear prediction, Lyapunov exponent estimation, and false nearest neighbors. It is concluded that even though the methods have problems and occasionally may be inconclusive, when correctly applied they are effective in delineating the dynamics underlying the data.</description><subject>Autocorrelation</subject><subject>Chaos theory</subject><subject>Dynamical systems</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>Geophysics. Techniques, methods, instrumentation and models</subject><subject>Meteorology</subject><subject>Neighborhoods</subject><subject>Series convergence</subject><subject>Spectral index</subject><subject>Time series</subject><subject>Time series forecasting</subject><subject>Time series models</subject><issn>0003-0007</issn><issn>1520-0477</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1994</creationdate><recordtype>article</recordtype><recordid>eNqFkd9rFDEQx4MoeLb9E4QgIvqw10mymx8qwnLa9qC6LxUfQ3YvsTn2kprsFe6_N8uVe_DFlwyT-eQ7mfkidElgSYhoLklDoYJaiPdEqfoDiOYz4ZR9bNfdXdt9oUtYrrpP9BlanMjnaAEArCqHeIle5bydUybJAv1qA16HR5sn_9tMPgYcHZ7uLW57P_rpMKc_Yhh9sCbh73a6j5uMp1geOZvw10MwOz9k7FLc4a7PNj2afrT5HL1wZsz24imeoZ9X3-5WN9Vtd71etbfVwBo2VYPhQKQzlPX1ppEceiG5MsBoL0DIjeqlcRthWC-JcwYc0GZorLHWSE4tZWfo3VH3IcU_-zKG3vk82HE0wcZ91kQSqTjjBXzzD7iN-xTK3zRllDOllPg_JEEW6PoIDSnmnKzTD8nvTDpoAnq2SM-L1_Pi9WyRhvmqWKSPFmmqQa9KKEpvn9qZPJjRJRMGn09yNeU1kBl7fcS2eYrpVKZFkijO2V9OFJzW</recordid><startdate>19940901</startdate><enddate>19940901</enddate><creator>Tsonis, A. A.</creator><creator>Triantafyllou, G. N.</creator><creator>Elsner, J. B.</creator><creator>Holdzkom, J. J.</creator><creator>Kirwan, A. D.</creator><general>American Meteorological Society</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>3V.</scope><scope>7XB</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>M2O</scope><scope>M2P</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>R05</scope><scope>S0X</scope></search><sort><creationdate>19940901</creationdate><title>An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables</title><author>Tsonis, A. A. ; Triantafyllou, G. N. ; Elsner, J. B. ; Holdzkom, J. J. ; Kirwan, A. D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-ca6018fa23b4d5860b7869a032b7078d9b8afd7a3b81ffa0f025c5eaeea862e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Autocorrelation</topic><topic>Chaos theory</topic><topic>Dynamical systems</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>External geophysics</topic><topic>Geophysics. Techniques, methods, instrumentation and models</topic><topic>Meteorology</topic><topic>Neighborhoods</topic><topic>Series convergence</topic><topic>Spectral index</topic><topic>Time series</topic><topic>Time series forecasting</topic><topic>Time series models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tsonis, A. A.</creatorcontrib><creatorcontrib>Triantafyllou, G. N.</creatorcontrib><creatorcontrib>Elsner, J. B.</creatorcontrib><creatorcontrib>Holdzkom, J. J.</creatorcontrib><creatorcontrib>Kirwan, A. D.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Research Library</collection><collection>ProQuest Science Journals</collection><collection>Research Library (Corporate)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>University of Michigan</collection><collection>SIRS Editorial</collection><jtitle>Bulletin of the American Meteorological Society</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tsonis, A. A.</au><au>Triantafyllou, G. N.</au><au>Elsner, J. B.</au><au>Holdzkom, J. J.</au><au>Kirwan, A. D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables</atitle><jtitle>Bulletin of the American Meteorological Society</jtitle><date>1994-09-01</date><risdate>1994</risdate><volume>75</volume><issue>9</issue><spage>1623</spage><epage>1633</epage><pages>1623-1633</pages><issn>0003-0007</issn><eissn>1520-0477</eissn><coden>BAMOAD</coden><abstract>In this study analysis of data whose character was kept secret was performed by employing a variety of nonlinear approaches. The idea was to test the ability of approaches stemming from the theory of nonlinear dynamical systems to infer the true properties hidden in the data. The approaches employed include dimension estimation, nonlinear prediction, Lyapunov exponent estimation, and false nearest neighbors. It is concluded that even though the methods have problems and occasionally may be inconclusive, when correctly applied they are effective in delineating the dynamics underlying the data.</abstract><cop>Boston, MA</cop><pub>American Meteorological Society</pub><doi>10.1175/1520-0477(1994)075<1623:AIOTAO>2.0.CO;2</doi><tpages>11</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0003-0007 |
| ispartof | Bulletin of the American Meteorological Society, 1994-09, Vol.75 (9), p.1623-1633 |
| issn | 0003-0007 1520-0477 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_18189636 |
| source | JSTOR Archival Journals and Primary Sources Collection |
| subjects | Autocorrelation Chaos theory Dynamical systems Earth, ocean, space Exact sciences and technology External geophysics Geophysics. Techniques, methods, instrumentation and models Meteorology Neighborhoods Series convergence Spectral index Time series Time series forecasting Time series models |
| title | An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T14%3A32%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Investigation%20of%20the%20Ability%20of%20Nonlinear%20Methods%20to%20Infer%20Dynamics%20from%20Observables&rft.jtitle=Bulletin%20of%20the%20American%20Meteorological%20Society&rft.au=Tsonis,%20A.%20A.&rft.date=1994-09-01&rft.volume=75&rft.issue=9&rft.spage=1623&rft.epage=1633&rft.pages=1623-1633&rft.issn=0003-0007&rft.eissn=1520-0477&rft.coden=BAMOAD&rft_id=info:doi/10.1175/1520-0477(1994)075%3C1623:AIOTAO%3E2.0.CO;2&rft_dat=%3Cjstor_proqu%3E26231966%3C/jstor_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c353t-ca6018fa23b4d5860b7869a032b7078d9b8afd7a3b81ffa0f025c5eaeea862e23%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=232639997&rft_id=info:pmid/&rft_jstor_id=26231966&rfr_iscdi=true |