Independence Testing for Multivariate Time Series Article Swipe
Ronak Mehta
,
Jaewon Chung
,
Cencheng Shen
,
Ting Xu
,
Joshua T Vogelstein
·
YOU?
·
· 2019
· Open Access
·
YOU?
·
· 2019
· Open Access
·
Complex data structures such as time series are increasingly present in modern data science problems. A fundamental question is whether two such time-series are statistically dependent. Many current approaches make parametric assumptions on the random processes, only detect linear association, require multiple tests, or forfeit power in high-dimensional, nonlinear settings. Estimating the distribution of any test statistic under the null is non-trivial, as the permutation test is invalid. This work juxtaposes distance correlation (Dcorr) and multiscale graph correlation (MGC) from independence testing literature and block permutation from time series analysis to address these challenges. The proposed nonparametric procedure is valid and consistent, building upon prior work by characterizing the geometry of the relationship, estimating the time lag at which dependence is maximized, avoiding the need for multiple testing, and exhibiting superior power in high-dimensional, low sample size, nonlinear settings. Neural connectivity is analyzed via fMRI data, revealing linear dependence of signals within the visual network and default mode network, and nonlinear relationships in other networks. This work uncovers a first-resort data analysis tool with open-source code available, directly impacting a wide range of scientific disciplines.
Related Topics
Concepts
Permutation (music)
Multivariate statistics
Computer science
Test statistic
Nonparametric statistics
Time series
Statistic
Independence (probability theory)
Nonlinear system
Series (stratigraphy)
Range (aeronautics)
Statistical hypothesis testing
Algorithm
Data mining
Mathematics
Statistics
Machine learning
Engineering
Acoustics
Physics
Aerospace engineering
Quantum mechanics
Biology
Paleontology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://arxiv.org/pdf/1908.06486v3
- OA Status
- green
- Cited By
- 3
- References
- 20
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3024152454
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3024152454Canonical identifier for this work in OpenAlex
- Title
-
Independence Testing for Multivariate Time SeriesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-08-18Full publication date if available
- Authors
-
Ronak Mehta, Jaewon Chung, Cencheng Shen, Ting Xu, Joshua T VogelsteinList of authors in order
- Landing page
-
https://arxiv.org/pdf/1908.06486v3Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1908.06486v3Direct OA link when available
- Concepts
-
Permutation (music), Multivariate statistics, Computer science, Test statistic, Nonparametric statistics, Time series, Statistic, Independence (probability theory), Nonlinear system, Series (stratigraphy), Range (aeronautics), Statistical hypothesis testing, Algorithm, Data mining, Mathematics, Statistics, Machine learning, Engineering, Acoustics, Physics, Aerospace engineering, Quantum mechanics, Biology, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2020: 1, 2019: 1, 2018: 1Per-year citation counts (last 5 years)
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3024152454 |
|---|---|
| doi | |
| ids.mag | 3024152454 |
| ids.openalex | https://openalex.org/W3024152454 |
| fwci | |
| type | preprint |
| title | Independence Testing for Multivariate Time Series |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10241 |
| topics[0].field.id | https://openalex.org/fields/28 |
| topics[0].field.display_name | Neuroscience |
| topics[0].score | 0.9993000030517578 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2805 |
| topics[0].subfield.display_name | Cognitive Neuroscience |
| topics[0].display_name | Functional Brain Connectivity Studies |
| topics[1].id | https://openalex.org/T11270 |
| topics[1].field.id | https://openalex.org/fields/20 |
| topics[1].field.display_name | Economics, Econometrics and Finance |
| topics[1].score | 0.9951000213623047 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2002 |
| topics[1].subfield.display_name | Economics and Econometrics |
| topics[1].display_name | Complex Systems and Time Series Analysis |
| topics[2].id | https://openalex.org/T10581 |
| topics[2].field.id | https://openalex.org/fields/28 |
| topics[2].field.display_name | Neuroscience |
| topics[2].score | 0.9916999936103821 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2805 |
| topics[2].subfield.display_name | Cognitive Neuroscience |
| topics[2].display_name | Neural dynamics and brain function |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C21308566 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5739291310310364 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q7169365 |
| concepts[0].display_name | Permutation (music) |
| concepts[1].id | https://openalex.org/C161584116 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5657378435134888 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1952580 |
| concepts[1].display_name | Multivariate statistics |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5390097498893738 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C169857963 |
| concepts[3].level | 3 |
| concepts[3].score | 0.5151726007461548 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1461038 |
| concepts[3].display_name | Test statistic |
| concepts[4].id | https://openalex.org/C102366305 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5141956806182861 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1097688 |
| concepts[4].display_name | Nonparametric statistics |
| concepts[5].id | https://openalex.org/C151406439 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4986250400543213 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q186588 |
| concepts[5].display_name | Time series |
| concepts[6].id | https://openalex.org/C89128539 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4954334497451782 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1949963 |
| concepts[6].display_name | Statistic |
| concepts[7].id | https://openalex.org/C35651441 |
| concepts[7].level | 2 |
| concepts[7].score | 0.47350484132766724 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q625303 |
| concepts[7].display_name | Independence (probability theory) |
| concepts[8].id | https://openalex.org/C158622935 |
| concepts[8].level | 2 |
| concepts[8].score | 0.47103244066238403 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q660848 |
| concepts[8].display_name | Nonlinear system |
| concepts[9].id | https://openalex.org/C143724316 |
| concepts[9].level | 2 |
| concepts[9].score | 0.45419907569885254 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q312468 |
| concepts[9].display_name | Series (stratigraphy) |
| concepts[10].id | https://openalex.org/C204323151 |
| concepts[10].level | 2 |
| concepts[10].score | 0.43239760398864746 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q905424 |
| concepts[10].display_name | Range (aeronautics) |
| concepts[11].id | https://openalex.org/C87007009 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4248512089252472 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q210832 |
| concepts[11].display_name | Statistical hypothesis testing |
| concepts[12].id | https://openalex.org/C11413529 |
| concepts[12].level | 1 |
| concepts[12].score | 0.39291107654571533 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[12].display_name | Algorithm |
| concepts[13].id | https://openalex.org/C124101348 |
| concepts[13].level | 1 |
| concepts[13].score | 0.37783387303352356 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[13].display_name | Data mining |
| concepts[14].id | https://openalex.org/C33923547 |
| concepts[14].level | 0 |
| concepts[14].score | 0.3199560046195984 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[14].display_name | Mathematics |
| concepts[15].id | https://openalex.org/C105795698 |
| concepts[15].level | 1 |
| concepts[15].score | 0.2956632971763611 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[15].display_name | Statistics |
| concepts[16].id | https://openalex.org/C119857082 |
| concepts[16].level | 1 |
| concepts[16].score | 0.2532271146774292 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[16].display_name | Machine learning |
| concepts[17].id | https://openalex.org/C127413603 |
| concepts[17].level | 0 |
| concepts[17].score | 0.09644964337348938 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[17].display_name | Engineering |
| concepts[18].id | https://openalex.org/C24890656 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q82811 |
| concepts[18].display_name | Acoustics |
| concepts[19].id | https://openalex.org/C121332964 |
| concepts[19].level | 0 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[19].display_name | Physics |
| concepts[20].id | https://openalex.org/C146978453 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q3798668 |
| concepts[20].display_name | Aerospace engineering |
| concepts[21].id | https://openalex.org/C62520636 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[21].display_name | Quantum mechanics |
| concepts[22].id | https://openalex.org/C86803240 |
| concepts[22].level | 0 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[22].display_name | Biology |
| concepts[23].id | https://openalex.org/C151730666 |
| concepts[23].level | 1 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[23].display_name | Paleontology |
| keywords[0].id | https://openalex.org/keywords/permutation |
| keywords[0].score | 0.5739291310310364 |
| keywords[0].display_name | Permutation (music) |
| keywords[1].id | https://openalex.org/keywords/multivariate-statistics |
| keywords[1].score | 0.5657378435134888 |
| keywords[1].display_name | Multivariate statistics |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.5390097498893738 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/test-statistic |
| keywords[3].score | 0.5151726007461548 |
| keywords[3].display_name | Test statistic |
| keywords[4].id | https://openalex.org/keywords/nonparametric-statistics |
| keywords[4].score | 0.5141956806182861 |
| keywords[4].display_name | Nonparametric statistics |
| keywords[5].id | https://openalex.org/keywords/time-series |
| keywords[5].score | 0.4986250400543213 |
| keywords[5].display_name | Time series |
| keywords[6].id | https://openalex.org/keywords/statistic |
| keywords[6].score | 0.4954334497451782 |
| keywords[6].display_name | Statistic |
| keywords[7].id | https://openalex.org/keywords/independence |
| keywords[7].score | 0.47350484132766724 |
| keywords[7].display_name | Independence (probability theory) |
| keywords[8].id | https://openalex.org/keywords/nonlinear-system |
| keywords[8].score | 0.47103244066238403 |
| keywords[8].display_name | Nonlinear system |
| keywords[9].id | https://openalex.org/keywords/series |
| keywords[9].score | 0.45419907569885254 |
| keywords[9].display_name | Series (stratigraphy) |
| keywords[10].id | https://openalex.org/keywords/range |
| keywords[10].score | 0.43239760398864746 |
| keywords[10].display_name | Range (aeronautics) |
| keywords[11].id | https://openalex.org/keywords/statistical-hypothesis-testing |
| keywords[11].score | 0.4248512089252472 |
| keywords[11].display_name | Statistical hypothesis testing |
| keywords[12].id | https://openalex.org/keywords/algorithm |
| keywords[12].score | 0.39291107654571533 |
| keywords[12].display_name | Algorithm |
| keywords[13].id | https://openalex.org/keywords/data-mining |
| keywords[13].score | 0.37783387303352356 |
| keywords[13].display_name | Data mining |
| keywords[14].id | https://openalex.org/keywords/mathematics |
| keywords[14].score | 0.3199560046195984 |
| keywords[14].display_name | Mathematics |
| keywords[15].id | https://openalex.org/keywords/statistics |
| keywords[15].score | 0.2956632971763611 |
| keywords[15].display_name | Statistics |
| keywords[16].id | https://openalex.org/keywords/machine-learning |
| keywords[16].score | 0.2532271146774292 |
| keywords[16].display_name | Machine learning |
| keywords[17].id | https://openalex.org/keywords/engineering |
| keywords[17].score | 0.09644964337348938 |
| keywords[17].display_name | Engineering |
| language | en |
| locations[0].id | mag:3024152454 |
| 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 | |
| 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 | arXiv (Cornell University) |
| locations[0].landing_page_url | https://arxiv.org/pdf/1908.06486v3 |
| authorships[0].author.id | https://openalex.org/A5001083519 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Ronak Mehta |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ronak Mehta |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5064683530 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-8940-3417 |
| authorships[1].author.display_name | Jaewon Chung |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Jaewon Chung |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5017159636 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-1030-1432 |
| authorships[2].author.display_name | Cencheng Shen |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Cencheng Shen |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5035475292 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-1590-9025 |
| authorships[3].author.display_name | Ting Xu |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Ting Xu |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5065441417 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-2487-6237 |
| authorships[4].author.display_name | Joshua T Vogelstein |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Joshua T. Vogelstein |
| authorships[4].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/1908.06486v3 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Independence Testing for Multivariate Time Series |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-10-10T17:16:08.811792 |
| primary_topic.id | https://openalex.org/T10241 |
| primary_topic.field.id | https://openalex.org/fields/28 |
| primary_topic.field.display_name | Neuroscience |
| primary_topic.score | 0.9993000030517578 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2805 |
| primary_topic.subfield.display_name | Cognitive Neuroscience |
| primary_topic.display_name | Functional Brain Connectivity Studies |
| related_works | https://openalex.org/W2968691680, https://openalex.org/W2276655326, https://openalex.org/W3109648049, https://openalex.org/W3038536661, https://openalex.org/W2099823040, https://openalex.org/W2967994127, https://openalex.org/W2779821539, https://openalex.org/W2951376723, https://openalex.org/W2772976064, https://openalex.org/W3038344117, https://openalex.org/W1681398360, https://openalex.org/W3123830776, https://openalex.org/W3195659235, https://openalex.org/W3127958088, https://openalex.org/W2898553479, https://openalex.org/W2184419302, https://openalex.org/W3046824338, https://openalex.org/W3102427176, https://openalex.org/W2105230408, https://openalex.org/W3100980645 |
| cited_by_count | 3 |
| counts_by_year[0].year | 2020 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2019 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2018 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | mag:3024152454 |
| 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 | |
| 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 | arXiv (Cornell University) |
| best_oa_location.landing_page_url | https://arxiv.org/pdf/1908.06486v3 |
| primary_location.id | mag:3024152454 |
| 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 | |
| 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 | arXiv (Cornell University) |
| primary_location.landing_page_url | https://arxiv.org/pdf/1908.06486v3 |
| publication_date | 2019-08-18 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W3089526752, https://openalex.org/W2980871794, https://openalex.org/W2141482776, https://openalex.org/W2023205960, https://openalex.org/W2076876316, https://openalex.org/W2044192590, https://openalex.org/W1518726585, https://openalex.org/W1779010541, https://openalex.org/W2499800833, https://openalex.org/W171990073, https://openalex.org/W2018411636, https://openalex.org/W2951830198, https://openalex.org/W2979012257, https://openalex.org/W2963348597, https://openalex.org/W2145544165, https://openalex.org/W1985271258, https://openalex.org/W2412664745, https://openalex.org/W2798942556, https://openalex.org/W2167663973, https://openalex.org/W2951581451 |
| referenced_works_count | 20 |
| abstract_inverted_index.A | 15 |
| abstract_inverted_index.a | 168, 179 |
| abstract_inverted_index.as | 4, 62 |
| abstract_inverted_index.at | 117 |
| abstract_inverted_index.by | 106 |
| abstract_inverted_index.in | 10, 46, 132, 162 |
| abstract_inverted_index.is | 18, 60, 66, 98, 120, 141 |
| abstract_inverted_index.of | 53, 110, 149, 182 |
| abstract_inverted_index.on | 32 |
| abstract_inverted_index.or | 43 |
| abstract_inverted_index.to | 90 |
| abstract_inverted_index.The | 94 |
| abstract_inverted_index.and | 74, 83, 100, 128, 155, 159 |
| abstract_inverted_index.any | 54 |
| abstract_inverted_index.are | 7, 23 |
| abstract_inverted_index.for | 125 |
| abstract_inverted_index.lag | 116 |
| abstract_inverted_index.low | 134 |
| abstract_inverted_index.the | 33, 51, 58, 63, 108, 111, 114, 123, 152 |
| abstract_inverted_index.two | 20 |
| abstract_inverted_index.via | 143 |
| abstract_inverted_index.Many | 26 |
| abstract_inverted_index.This | 68, 165 |
| abstract_inverted_index.code | 175 |
| abstract_inverted_index.data | 1, 12, 170 |
| abstract_inverted_index.fMRI | 144 |
| abstract_inverted_index.from | 79, 86 |
| abstract_inverted_index.make | 29 |
| abstract_inverted_index.mode | 157 |
| abstract_inverted_index.need | 124 |
| abstract_inverted_index.null | 59 |
| abstract_inverted_index.only | 36 |
| abstract_inverted_index.such | 3, 21 |
| abstract_inverted_index.test | 55, 65 |
| abstract_inverted_index.time | 5, 87, 115 |
| abstract_inverted_index.tool | 172 |
| abstract_inverted_index.upon | 103 |
| abstract_inverted_index.wide | 180 |
| abstract_inverted_index.with | 173 |
| abstract_inverted_index.work | 69, 105, 166 |
| abstract_inverted_index.(MGC) | 78 |
| abstract_inverted_index.block | 84 |
| abstract_inverted_index.data, | 145 |
| abstract_inverted_index.graph | 76 |
| abstract_inverted_index.other | 163 |
| abstract_inverted_index.power | 45, 131 |
| abstract_inverted_index.prior | 104 |
| abstract_inverted_index.range | 181 |
| abstract_inverted_index.size, | 136 |
| abstract_inverted_index.these | 92 |
| abstract_inverted_index.under | 57 |
| abstract_inverted_index.valid | 99 |
| abstract_inverted_index.which | 118 |
| abstract_inverted_index.Neural | 139 |
| abstract_inverted_index.detect | 37 |
| abstract_inverted_index.linear | 38, 147 |
| abstract_inverted_index.modern | 11 |
| abstract_inverted_index.random | 34 |
| abstract_inverted_index.sample | 135 |
| abstract_inverted_index.series | 6, 88 |
| abstract_inverted_index.tests, | 42 |
| abstract_inverted_index.visual | 153 |
| abstract_inverted_index.within | 151 |
| abstract_inverted_index.(Dcorr) | 73 |
| abstract_inverted_index.Complex | 0 |
| abstract_inverted_index.address | 91 |
| abstract_inverted_index.current | 27 |
| abstract_inverted_index.default | 156 |
| abstract_inverted_index.forfeit | 44 |
| abstract_inverted_index.network | 154 |
| abstract_inverted_index.present | 9 |
| abstract_inverted_index.require | 40 |
| abstract_inverted_index.science | 13 |
| abstract_inverted_index.signals | 150 |
| abstract_inverted_index.testing | 81 |
| abstract_inverted_index.whether | 19 |
| abstract_inverted_index.analysis | 89, 171 |
| abstract_inverted_index.analyzed | 142 |
| abstract_inverted_index.avoiding | 122 |
| abstract_inverted_index.building | 102 |
| abstract_inverted_index.directly | 177 |
| abstract_inverted_index.distance | 71 |
| abstract_inverted_index.geometry | 109 |
| abstract_inverted_index.invalid. | 67 |
| abstract_inverted_index.multiple | 41, 126 |
| abstract_inverted_index.network, | 158 |
| abstract_inverted_index.proposed | 95 |
| abstract_inverted_index.question | 17 |
| abstract_inverted_index.superior | 130 |
| abstract_inverted_index.testing, | 127 |
| abstract_inverted_index.uncovers | 167 |
| abstract_inverted_index.impacting | 178 |
| abstract_inverted_index.networks. | 164 |
| abstract_inverted_index.nonlinear | 48, 137, 160 |
| abstract_inverted_index.problems. | 14 |
| abstract_inverted_index.procedure | 97 |
| abstract_inverted_index.revealing | 146 |
| abstract_inverted_index.settings. | 49, 138 |
| abstract_inverted_index.statistic | 56 |
| abstract_inverted_index.Estimating | 50 |
| abstract_inverted_index.approaches | 28 |
| abstract_inverted_index.available, | 176 |
| abstract_inverted_index.dependence | 119, 148 |
| abstract_inverted_index.dependent. | 25 |
| abstract_inverted_index.estimating | 113 |
| abstract_inverted_index.exhibiting | 129 |
| abstract_inverted_index.juxtaposes | 70 |
| abstract_inverted_index.literature | 82 |
| abstract_inverted_index.maximized, | 121 |
| abstract_inverted_index.multiscale | 75 |
| abstract_inverted_index.parametric | 30 |
| abstract_inverted_index.processes, | 35 |
| abstract_inverted_index.scientific | 183 |
| abstract_inverted_index.structures | 2 |
| abstract_inverted_index.assumptions | 31 |
| abstract_inverted_index.challenges. | 93 |
| abstract_inverted_index.consistent, | 101 |
| abstract_inverted_index.correlation | 72, 77 |
| abstract_inverted_index.fundamental | 16 |
| abstract_inverted_index.open-source | 174 |
| abstract_inverted_index.permutation | 64, 85 |
| abstract_inverted_index.time-series | 22 |
| abstract_inverted_index.association, | 39 |
| abstract_inverted_index.connectivity | 140 |
| abstract_inverted_index.disciplines. | 184 |
| abstract_inverted_index.distribution | 52 |
| abstract_inverted_index.first-resort | 169 |
| abstract_inverted_index.increasingly | 8 |
| abstract_inverted_index.independence | 80 |
| abstract_inverted_index.non-trivial, | 61 |
| abstract_inverted_index.nonparametric | 96 |
| abstract_inverted_index.relationship, | 112 |
| abstract_inverted_index.relationships | 161 |
| abstract_inverted_index.statistically | 24 |
| abstract_inverted_index.characterizing | 107 |
| abstract_inverted_index.high-dimensional, | 47, 133 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |