Parameter Estimation in Models with Complex Dynamics Article Swipe
Abhirup Ghosh
,
Samit Bhattacharyya
,
Somdatta Sinha
,
Amit Apte
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1705.03868
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1705.03868
Mathematical models of real life phenomena are highly nonlinear involving multiple parameters and often exhibiting complex dynamics. Experimental data sets are typically small and noisy, rendering estimation of parameters from such data unreliable and difficult. This paper presents a study of the Bayesian posterior distribution for unknown parameters of two chaotic discrete dynamical systems conditioned on observations of the system. The study shows how the qualitative properties of the posterior are affected by the intrinsic noise present in the data, the representation of this noise in the parameter estimation process, and the length of the data-set. The results indicate that increasing length of dataset does not significantly increase the precision of the estimate, and this is true for both periodic and chaotic data. On the other hand, increasing precision of the measurements leads to significant increase in precision of the estimated parameter in case of periodic data, but not in the case of chaotic data. These results are highly useful in designing laboratory and field-based studies in biology in general, and ecology and conservation in particular.
Related Topics
Concepts
Chaotic
Rendering (computer graphics)
Estimation theory
Computer science
Noise (video)
Bayesian probability
Nonlinear system
Data set
Representation (politics)
Algorithm
Statistical physics
Data mining
Mathematics
Artificial intelligence
Physics
Politics
Quantum mechanics
Law
Political science
Image (mathematics)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1705.03868
- https://arxiv.org/pdf/1705.03868
- OA Status
- green
- References
- 53
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2613514135
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2613514135Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1705.03868Digital Object Identifier
- Title
-
Parameter Estimation in Models with Complex DynamicsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-05-10Full publication date if available
- Authors
-
Abhirup Ghosh, Samit Bhattacharyya, Somdatta Sinha, Amit ApteList of authors in order
- Landing page
-
https://arxiv.org/abs/1705.03868Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1705.03868Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1705.03868Direct OA link when available
- Concepts
-
Chaotic, Rendering (computer graphics), Estimation theory, Computer science, Noise (video), Bayesian probability, Nonlinear system, Data set, Representation (politics), Algorithm, Statistical physics, Data mining, Mathematics, Artificial intelligence, Physics, Politics, Quantum mechanics, Law, Political science, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
53Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2613514135 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.1705.03868 |
| ids.doi | https://doi.org/10.48550/arxiv.1705.03868 |
| ids.mag | 2613514135 |
| ids.openalex | https://openalex.org/W2613514135 |
| fwci | |
| type | preprint |
| title | Parameter Estimation in Models with Complex Dynamics |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10895 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.9416999816894531 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2302 |
| topics[0].subfield.display_name | Ecological Modeling |
| topics[0].display_name | Species Distribution and Climate Change |
| topics[1].id | https://openalex.org/T11764 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9380000233650208 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1311 |
| topics[1].subfield.display_name | Genetics |
| topics[1].display_name | Evolution and Genetic Dynamics |
| topics[2].id | https://openalex.org/T10320 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9365000128746033 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Neural Networks and Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2777052490 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6790658235549927 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5072826 |
| concepts[0].display_name | Chaotic |
| concepts[1].id | https://openalex.org/C205711294 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6008341908454895 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q176953 |
| concepts[1].display_name | Rendering (computer graphics) |
| concepts[2].id | https://openalex.org/C167928553 |
| concepts[2].level | 2 |
| concepts[2].score | 0.579374372959137 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1376021 |
| concepts[2].display_name | Estimation theory |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5638895034790039 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C99498987 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5103806853294373 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2210247 |
| concepts[4].display_name | Noise (video) |
| concepts[5].id | https://openalex.org/C107673813 |
| concepts[5].level | 2 |
| concepts[5].score | 0.49133720993995667 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q812534 |
| concepts[5].display_name | Bayesian probability |
| concepts[6].id | https://openalex.org/C158622935 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4817816913127899 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q660848 |
| concepts[6].display_name | Nonlinear system |
| concepts[7].id | https://openalex.org/C58489278 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4521874487400055 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1172284 |
| concepts[7].display_name | Data set |
| concepts[8].id | https://openalex.org/C2776359362 |
| concepts[8].level | 3 |
| concepts[8].score | 0.43684515357017517 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2145286 |
| concepts[8].display_name | Representation (politics) |
| concepts[9].id | https://openalex.org/C11413529 |
| concepts[9].level | 1 |
| concepts[9].score | 0.42478641867637634 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[9].display_name | Algorithm |
| concepts[10].id | https://openalex.org/C121864883 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3648805618286133 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q677916 |
| concepts[10].display_name | Statistical physics |
| concepts[11].id | https://openalex.org/C124101348 |
| concepts[11].level | 1 |
| concepts[11].score | 0.3393585681915283 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[11].display_name | Data mining |
| concepts[12].id | https://openalex.org/C33923547 |
| concepts[12].level | 0 |
| concepts[12].score | 0.321219801902771 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[12].display_name | Mathematics |
| concepts[13].id | https://openalex.org/C154945302 |
| concepts[13].level | 1 |
| concepts[13].score | 0.20694991946220398 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[13].display_name | Artificial intelligence |
| concepts[14].id | https://openalex.org/C121332964 |
| concepts[14].level | 0 |
| concepts[14].score | 0.13384151458740234 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[14].display_name | Physics |
| concepts[15].id | https://openalex.org/C94625758 |
| concepts[15].level | 2 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7163 |
| concepts[15].display_name | Politics |
| concepts[16].id | https://openalex.org/C62520636 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[16].display_name | Quantum mechanics |
| concepts[17].id | https://openalex.org/C199539241 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[17].display_name | Law |
| concepts[18].id | https://openalex.org/C17744445 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[18].display_name | Political science |
| concepts[19].id | https://openalex.org/C115961682 |
| concepts[19].level | 2 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[19].display_name | Image (mathematics) |
| keywords[0].id | https://openalex.org/keywords/chaotic |
| keywords[0].score | 0.6790658235549927 |
| keywords[0].display_name | Chaotic |
| keywords[1].id | https://openalex.org/keywords/rendering |
| keywords[1].score | 0.6008341908454895 |
| keywords[1].display_name | Rendering (computer graphics) |
| keywords[2].id | https://openalex.org/keywords/estimation-theory |
| keywords[2].score | 0.579374372959137 |
| keywords[2].display_name | Estimation theory |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.5638895034790039 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/noise |
| keywords[4].score | 0.5103806853294373 |
| keywords[4].display_name | Noise (video) |
| keywords[5].id | https://openalex.org/keywords/bayesian-probability |
| keywords[5].score | 0.49133720993995667 |
| keywords[5].display_name | Bayesian probability |
| keywords[6].id | https://openalex.org/keywords/nonlinear-system |
| keywords[6].score | 0.4817816913127899 |
| keywords[6].display_name | Nonlinear system |
| keywords[7].id | https://openalex.org/keywords/data-set |
| keywords[7].score | 0.4521874487400055 |
| keywords[7].display_name | Data set |
| keywords[8].id | https://openalex.org/keywords/representation |
| keywords[8].score | 0.43684515357017517 |
| keywords[8].display_name | Representation (politics) |
| keywords[9].id | https://openalex.org/keywords/algorithm |
| keywords[9].score | 0.42478641867637634 |
| keywords[9].display_name | Algorithm |
| keywords[10].id | https://openalex.org/keywords/statistical-physics |
| keywords[10].score | 0.3648805618286133 |
| keywords[10].display_name | Statistical physics |
| keywords[11].id | https://openalex.org/keywords/data-mining |
| keywords[11].score | 0.3393585681915283 |
| keywords[11].display_name | Data mining |
| keywords[12].id | https://openalex.org/keywords/mathematics |
| keywords[12].score | 0.321219801902771 |
| keywords[12].display_name | Mathematics |
| keywords[13].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[13].score | 0.20694991946220398 |
| keywords[13].display_name | Artificial intelligence |
| keywords[14].id | https://openalex.org/keywords/physics |
| keywords[14].score | 0.13384151458740234 |
| keywords[14].display_name | Physics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:1705.03868 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/1705.03868 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/1705.03868 |
| locations[1].id | mag:2613514135 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | arXiv (Cornell University) |
| locations[1].landing_page_url | http://arxiv.org/pdf/1705.03868.pdf |
| locations[2].id | doi:10.48550/arxiv.1705.03868 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306400194 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | True |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | arXiv (Cornell University) |
| locations[2].source.host_organization | https://openalex.org/I205783295 |
| locations[2].source.host_organization_name | Cornell University |
| locations[2].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | |
| locations[2].raw_source_name | |
| locations[2].landing_page_url | https://doi.org/10.48550/arxiv.1705.03868 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5061565583 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-2112-8578 |
| authorships[0].author.display_name | Abhirup Ghosh |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Abhirup Ghosh |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5014056058 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-7357-7949 |
| authorships[1].author.display_name | Samit Bhattacharyya |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Samit Bhattacharyya |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5027764808 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3534-9651 |
| authorships[2].author.display_name | Somdatta Sinha |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Somdatta Sinha |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5054043071 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-3632-7553 |
| authorships[3].author.display_name | Amit Apte |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Amit Apte |
| authorships[3].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/1705.03868 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Parameter Estimation in Models with Complex Dynamics |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10895 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.9416999816894531 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2302 |
| primary_topic.subfield.display_name | Ecological Modeling |
| primary_topic.display_name | Species Distribution and Climate Change |
| related_works | https://openalex.org/W2083690581, https://openalex.org/W2092124742, https://openalex.org/W2107579288, https://openalex.org/W1820772924, https://openalex.org/W2173736524, https://openalex.org/W2741052609, https://openalex.org/W3082628064, https://openalex.org/W2074479337, https://openalex.org/W2980434614, https://openalex.org/W2884839891, https://openalex.org/W1836134433, https://openalex.org/W2585553556, https://openalex.org/W85179170, https://openalex.org/W2174630065, https://openalex.org/W1984938557, https://openalex.org/W2508265855, https://openalex.org/W3101015930, https://openalex.org/W2049907541, https://openalex.org/W2326001072, https://openalex.org/W795385116 |
| cited_by_count | 0 |
| locations_count | 3 |
| best_oa_location.id | pmh:oai:arXiv.org:1705.03868 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/1705.03868 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/1705.03868 |
| primary_location.id | pmh:oai:arXiv.org:1705.03868 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/1705.03868 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/1705.03868 |
| publication_date | 2017-05-10 |
| publication_year | 2017 |
| referenced_works | https://openalex.org/W2076957841, https://openalex.org/W2086935182, https://openalex.org/W2099142958, https://openalex.org/W2088567128, https://openalex.org/W3103934441, https://openalex.org/W2254226187, https://openalex.org/W2157913712, https://openalex.org/W1500551892, https://openalex.org/W2020684750, https://openalex.org/W2078054204, https://openalex.org/W2331300162, https://openalex.org/W402407836, https://openalex.org/W1964740397, https://openalex.org/W1596195796, https://openalex.org/W2102892532, https://openalex.org/W1990088328, https://openalex.org/W1985093013, https://openalex.org/W2111480264, https://openalex.org/W3099115132, https://openalex.org/W1920795497, https://openalex.org/W2016765436, https://openalex.org/W2168711358, https://openalex.org/W2064480843, https://openalex.org/W2039813141, https://openalex.org/W2187487057, https://openalex.org/W2079133700, https://openalex.org/W3101606534, https://openalex.org/W2128536454, https://openalex.org/W2089634494, https://openalex.org/W1501586228, https://openalex.org/W2268619227, https://openalex.org/W2019744409, https://openalex.org/W2039696702, https://openalex.org/W2027689606, https://openalex.org/W2034527082, https://openalex.org/W2034833340, https://openalex.org/W2070595746, https://openalex.org/W1963568208, https://openalex.org/W2161442523, https://openalex.org/W2119440996, https://openalex.org/W1999885564, https://openalex.org/W2057420782, https://openalex.org/W2134589175, https://openalex.org/W1984401686, https://openalex.org/W2132320458, https://openalex.org/W2110798438, https://openalex.org/W1029488735, https://openalex.org/W1967637715, https://openalex.org/W2148195527, https://openalex.org/W2044487285, https://openalex.org/W2150821867, https://openalex.org/W2114084375, https://openalex.org/W2085645016 |
| referenced_works_count | 53 |
| abstract_inverted_index.a | 38 |
| abstract_inverted_index.On | 123 |
| abstract_inverted_index.by | 72 |
| abstract_inverted_index.in | 77, 85, 136, 142, 149, 160, 166, 168, 174 |
| abstract_inverted_index.is | 115 |
| abstract_inverted_index.of | 2, 27, 40, 48, 57, 67, 82, 93, 102, 110, 129, 138, 144, 152 |
| abstract_inverted_index.on | 55 |
| abstract_inverted_index.to | 133 |
| abstract_inverted_index.The | 60, 96 |
| abstract_inverted_index.and | 12, 23, 33, 90, 113, 120, 163, 170, 172 |
| abstract_inverted_index.are | 6, 20, 70, 157 |
| abstract_inverted_index.but | 147 |
| abstract_inverted_index.for | 45, 117 |
| abstract_inverted_index.how | 63 |
| abstract_inverted_index.not | 105, 148 |
| abstract_inverted_index.the | 41, 58, 64, 68, 73, 78, 80, 86, 91, 94, 108, 111, 124, 130, 139, 150 |
| abstract_inverted_index.two | 49 |
| abstract_inverted_index.This | 35 |
| abstract_inverted_index.both | 118 |
| abstract_inverted_index.case | 143, 151 |
| abstract_inverted_index.data | 18, 31 |
| abstract_inverted_index.does | 104 |
| abstract_inverted_index.from | 29 |
| abstract_inverted_index.life | 4 |
| abstract_inverted_index.real | 3 |
| abstract_inverted_index.sets | 19 |
| abstract_inverted_index.such | 30 |
| abstract_inverted_index.that | 99 |
| abstract_inverted_index.this | 83, 114 |
| abstract_inverted_index.true | 116 |
| abstract_inverted_index.These | 155 |
| abstract_inverted_index.data, | 79, 146 |
| abstract_inverted_index.data. | 122, 154 |
| abstract_inverted_index.hand, | 126 |
| abstract_inverted_index.leads | 132 |
| abstract_inverted_index.noise | 75, 84 |
| abstract_inverted_index.often | 13 |
| abstract_inverted_index.other | 125 |
| abstract_inverted_index.paper | 36 |
| abstract_inverted_index.shows | 62 |
| abstract_inverted_index.small | 22 |
| abstract_inverted_index.study | 39, 61 |
| abstract_inverted_index.highly | 7, 158 |
| abstract_inverted_index.length | 92, 101 |
| abstract_inverted_index.models | 1 |
| abstract_inverted_index.noisy, | 24 |
| abstract_inverted_index.useful | 159 |
| abstract_inverted_index.biology | 167 |
| abstract_inverted_index.chaotic | 50, 121, 153 |
| abstract_inverted_index.complex | 15 |
| abstract_inverted_index.dataset | 103 |
| abstract_inverted_index.ecology | 171 |
| abstract_inverted_index.present | 76 |
| abstract_inverted_index.results | 97, 156 |
| abstract_inverted_index.studies | 165 |
| abstract_inverted_index.system. | 59 |
| abstract_inverted_index.systems | 53 |
| abstract_inverted_index.unknown | 46 |
| abstract_inverted_index.Bayesian | 42 |
| abstract_inverted_index.affected | 71 |
| abstract_inverted_index.discrete | 51 |
| abstract_inverted_index.general, | 169 |
| abstract_inverted_index.increase | 107, 135 |
| abstract_inverted_index.indicate | 98 |
| abstract_inverted_index.multiple | 10 |
| abstract_inverted_index.periodic | 119, 145 |
| abstract_inverted_index.presents | 37 |
| abstract_inverted_index.process, | 89 |
| abstract_inverted_index.data-set. | 95 |
| abstract_inverted_index.designing | 161 |
| abstract_inverted_index.dynamical | 52 |
| abstract_inverted_index.dynamics. | 16 |
| abstract_inverted_index.estimate, | 112 |
| abstract_inverted_index.estimated | 140 |
| abstract_inverted_index.intrinsic | 74 |
| abstract_inverted_index.involving | 9 |
| abstract_inverted_index.nonlinear | 8 |
| abstract_inverted_index.parameter | 87, 141 |
| abstract_inverted_index.phenomena | 5 |
| abstract_inverted_index.posterior | 43, 69 |
| abstract_inverted_index.precision | 109, 128, 137 |
| abstract_inverted_index.rendering | 25 |
| abstract_inverted_index.typically | 21 |
| abstract_inverted_index.difficult. | 34 |
| abstract_inverted_index.estimation | 26, 88 |
| abstract_inverted_index.exhibiting | 14 |
| abstract_inverted_index.increasing | 100, 127 |
| abstract_inverted_index.laboratory | 162 |
| abstract_inverted_index.parameters | 11, 28, 47 |
| abstract_inverted_index.properties | 66 |
| abstract_inverted_index.unreliable | 32 |
| abstract_inverted_index.conditioned | 54 |
| abstract_inverted_index.field-based | 164 |
| abstract_inverted_index.particular. | 175 |
| abstract_inverted_index.qualitative | 65 |
| abstract_inverted_index.significant | 134 |
| abstract_inverted_index.Experimental | 17 |
| abstract_inverted_index.Mathematical | 0 |
| abstract_inverted_index.conservation | 173 |
| abstract_inverted_index.distribution | 44 |
| abstract_inverted_index.measurements | 131 |
| abstract_inverted_index.observations | 56 |
| abstract_inverted_index.significantly | 106 |
| abstract_inverted_index.representation | 81 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.6600000262260437 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile |