A Flexible Probability Model for Proportion Data: Unit Gumbel Type-II Distribution, Development, Properties, Different Method of Estimations and Applications Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.17713/ajs.v52i2.1407
In explaining and forecasting real life scenarios, statistical distributions are very helpful. It is very important to select the best fitting statistical distribution for modelling data. In analysis of real world phenomena like in reliability and economics, we may finddistributions for bounded data observed as percentages, proportions or fractions (see, for example, Marshall and Olkin (2007)). In this context, in view of pertinent transformation on the Gumbel Type-II model, we suggest and study the unit Gumbel Type-II (UG-TII)model and explore few of its statistical characteristics. We also consider various methods of estimating the unknown parameters of UG-TII model from the frequentist perspective. Monte Carlo simulations are worked out in order to compare efficiency of suggestedestimation methods for small as well as large samples. The efficiency of estimators is measured using simulated samples in terms of their bias and mean square error. In the end, two datasets have been examined in attempt to validate the realistic possibilities ofnew model. In comparison to the six severe competitors.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.17713/ajs.v52i2.1407
- https://www.ajs.or.at/index.php/ajs/article/download/1407/786
- OA Status
- diamond
- Cited By
- 28
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4324099145
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4324099145Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.17713/ajs.v52i2.1407Digital Object Identifier
- Title
-
A Flexible Probability Model for Proportion Data: Unit Gumbel Type-II Distribution, Development, Properties, Different Method of Estimations and ApplicationsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-12Full publication date if available
- Authors
-
Anum Shafiq, Tabassum Naz Sindhu, Zawar Hussain, Josmar Mazucheli, Bruna AlvesList of authors in order
- Landing page
-
https://doi.org/10.17713/ajs.v52i2.1407Publisher landing page
- PDF URL
-
https://www.ajs.or.at/index.php/ajs/article/download/1407/786Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.ajs.or.at/index.php/ajs/article/download/1407/786Direct OA link when available
- Concepts
-
Gumbel distribution, Estimator, Frequentist inference, Mathematics, Statistics, Context (archaeology), Monte Carlo method, Transformation (genetics), Econometrics, Computer science, Extreme value theory, Bayesian probability, Bayesian inference, Paleontology, Gene, Chemistry, Biology, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
28Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 8, 2024: 19, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
41Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4324099145 |
|---|---|
| doi | https://doi.org/10.17713/ajs.v52i2.1407 |
| ids.doi | https://doi.org/10.17713/ajs.v52i2.1407 |
| ids.openalex | https://openalex.org/W4324099145 |
| fwci | 9.05769321 |
| type | article |
| title | A Flexible Probability Model for Proportion Data: Unit Gumbel Type-II Distribution, Development, Properties, Different Method of Estimations and Applications |
| biblio.issue | 2 |
| biblio.volume | 52 |
| biblio.last_page | 140 |
| biblio.first_page | 116 |
| topics[0].id | https://openalex.org/T11918 |
| topics[0].field.id | https://openalex.org/fields/18 |
| topics[0].field.display_name | Decision Sciences |
| topics[0].score | 0.9688000082969666 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1803 |
| topics[0].subfield.display_name | Management Science and Operations Research |
| topics[0].display_name | Forecasting Techniques and Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C137610916 |
| concepts[0].level | 3 |
| concepts[0].score | 0.8212209939956665 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1096862 |
| concepts[0].display_name | Gumbel distribution |
| concepts[1].id | https://openalex.org/C185429906 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7216958999633789 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1130160 |
| concepts[1].display_name | Estimator |
| concepts[2].id | https://openalex.org/C162376815 |
| concepts[2].level | 4 |
| concepts[2].score | 0.5994244813919067 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q2158281 |
| concepts[2].display_name | Frequentist inference |
| concepts[3].id | https://openalex.org/C33923547 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5174192190170288 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[3].display_name | Mathematics |
| concepts[4].id | https://openalex.org/C105795698 |
| concepts[4].level | 1 |
| concepts[4].score | 0.46544110774993896 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[4].display_name | Statistics |
| concepts[5].id | https://openalex.org/C2779343474 |
| concepts[5].level | 2 |
| concepts[5].score | 0.45148709416389465 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3109175 |
| concepts[5].display_name | Context (archaeology) |
| concepts[6].id | https://openalex.org/C19499675 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4426833391189575 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q232207 |
| concepts[6].display_name | Monte Carlo method |
| concepts[7].id | https://openalex.org/C204241405 |
| concepts[7].level | 3 |
| concepts[7].score | 0.42864957451820374 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q461499 |
| concepts[7].display_name | Transformation (genetics) |
| concepts[8].id | https://openalex.org/C149782125 |
| concepts[8].level | 1 |
| concepts[8].score | 0.38099801540374756 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q160039 |
| concepts[8].display_name | Econometrics |
| concepts[9].id | https://openalex.org/C41008148 |
| concepts[9].level | 0 |
| concepts[9].score | 0.3356310725212097 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[9].display_name | Computer science |
| concepts[10].id | https://openalex.org/C147581598 |
| concepts[10].level | 2 |
| concepts[10].score | 0.1883258819580078 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q729429 |
| concepts[10].display_name | Extreme value theory |
| concepts[11].id | https://openalex.org/C107673813 |
| concepts[11].level | 2 |
| concepts[11].score | 0.11290594935417175 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q812534 |
| concepts[11].display_name | Bayesian probability |
| concepts[12].id | https://openalex.org/C160234255 |
| concepts[12].level | 3 |
| concepts[12].score | 0.09624433517456055 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q812535 |
| concepts[12].display_name | Bayesian inference |
| concepts[13].id | https://openalex.org/C151730666 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[13].display_name | Paleontology |
| concepts[14].id | https://openalex.org/C104317684 |
| concepts[14].level | 2 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[14].display_name | Gene |
| concepts[15].id | https://openalex.org/C185592680 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q2329 |
| concepts[15].display_name | Chemistry |
| concepts[16].id | https://openalex.org/C86803240 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[16].display_name | Biology |
| concepts[17].id | https://openalex.org/C55493867 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q7094 |
| concepts[17].display_name | Biochemistry |
| keywords[0].id | https://openalex.org/keywords/gumbel-distribution |
| keywords[0].score | 0.8212209939956665 |
| keywords[0].display_name | Gumbel distribution |
| keywords[1].id | https://openalex.org/keywords/estimator |
| keywords[1].score | 0.7216958999633789 |
| keywords[1].display_name | Estimator |
| keywords[2].id | https://openalex.org/keywords/frequentist-inference |
| keywords[2].score | 0.5994244813919067 |
| keywords[2].display_name | Frequentist inference |
| keywords[3].id | https://openalex.org/keywords/mathematics |
| keywords[3].score | 0.5174192190170288 |
| keywords[3].display_name | Mathematics |
| keywords[4].id | https://openalex.org/keywords/statistics |
| keywords[4].score | 0.46544110774993896 |
| keywords[4].display_name | Statistics |
| keywords[5].id | https://openalex.org/keywords/context |
| keywords[5].score | 0.45148709416389465 |
| keywords[5].display_name | Context (archaeology) |
| keywords[6].id | https://openalex.org/keywords/monte-carlo-method |
| keywords[6].score | 0.4426833391189575 |
| keywords[6].display_name | Monte Carlo method |
| keywords[7].id | https://openalex.org/keywords/transformation |
| keywords[7].score | 0.42864957451820374 |
| keywords[7].display_name | Transformation (genetics) |
| keywords[8].id | https://openalex.org/keywords/econometrics |
| keywords[8].score | 0.38099801540374756 |
| keywords[8].display_name | Econometrics |
| keywords[9].id | https://openalex.org/keywords/computer-science |
| keywords[9].score | 0.3356310725212097 |
| keywords[9].display_name | Computer science |
| keywords[10].id | https://openalex.org/keywords/extreme-value-theory |
| keywords[10].score | 0.1883258819580078 |
| keywords[10].display_name | Extreme value theory |
| keywords[11].id | https://openalex.org/keywords/bayesian-probability |
| keywords[11].score | 0.11290594935417175 |
| keywords[11].display_name | Bayesian probability |
| keywords[12].id | https://openalex.org/keywords/bayesian-inference |
| keywords[12].score | 0.09624433517456055 |
| keywords[12].display_name | Bayesian inference |
| language | en |
| locations[0].id | doi:10.17713/ajs.v52i2.1407 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764411241 |
| locations[0].source.issn | 1026-597X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1026-597X |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Austrian Journal of Statistics |
| locations[0].source.host_organization | https://openalex.org/P4310317894 |
| locations[0].source.host_organization_name | Austrian Journal of Statistics |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310317894 |
| locations[0].source.host_organization_lineage_names | Austrian Journal of Statistics |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.ajs.or.at/index.php/ajs/article/download/1407/786 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Austrian Journal of Statistics |
| locations[0].landing_page_url | https://doi.org/10.17713/ajs.v52i2.1407 |
| locations[1].id | pmh:oai:doaj.org/article:d7db61a1aff549d9abeb46a78e3b5ac4 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Austrian Journal of Statistics, Vol 52, Iss 2 (2023) |
| locations[1].landing_page_url | https://doaj.org/article/d7db61a1aff549d9abeb46a78e3b5ac4 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5070937697 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-7186-7216 |
| authorships[0].author.display_name | Anum Shafiq |
| authorships[0].affiliations[0].raw_affiliation_string | School of Mathematics and Statistics |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Anum Shafiq |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Mathematics and Statistics |
| authorships[1].author.id | https://openalex.org/A5010255093 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9433-4981 |
| authorships[1].author.display_name | Tabassum Naz Sindhu |
| authorships[1].countries | PK |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I12469534 |
| authorships[1].affiliations[0].raw_affiliation_string | Quaid-i-Azam University |
| authorships[1].institutions[0].id | https://openalex.org/I12469534 |
| authorships[1].institutions[0].ror | https://ror.org/04s9hft57 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I12469534 |
| authorships[1].institutions[0].country_code | PK |
| authorships[1].institutions[0].display_name | Quaid-i-Azam University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Tabassum Naz Sindhu |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Quaid-i-Azam University |
| authorships[2].author.id | https://openalex.org/A5100626825 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-5109-3652 |
| authorships[2].author.display_name | Zawar Hussain |
| authorships[2].countries | PK |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I79839403 |
| authorships[2].affiliations[0].raw_affiliation_string | Cholistan University of Veterinary & Animal Sciences |
| authorships[2].institutions[0].id | https://openalex.org/I79839403 |
| authorships[2].institutions[0].ror | https://ror.org/00g325k81 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I79839403 |
| authorships[2].institutions[0].country_code | PK |
| authorships[2].institutions[0].display_name | University of Veterinary and Animal Sciences |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Zawar Hussain |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Cholistan University of Veterinary & Animal Sciences |
| authorships[3].author.id | https://openalex.org/A5086206210 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-6740-0445 |
| authorships[3].author.display_name | Josmar Mazucheli |
| authorships[3].countries | BR |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I123443094 |
| authorships[3].affiliations[0].raw_affiliation_string | Universidade Estadual de Maringá |
| authorships[3].institutions[0].id | https://openalex.org/I123443094 |
| authorships[3].institutions[0].ror | https://ror.org/04bqqa360 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I123443094 |
| authorships[3].institutions[0].country_code | BR |
| authorships[3].institutions[0].display_name | Universidade Estadual de Maringá |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Josmar Mazucheli |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Universidade Estadual de Maringá |
| authorships[4].author.id | https://openalex.org/A5029480577 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0080-2658 |
| authorships[4].author.display_name | Bruna Alves |
| authorships[4].countries | BR |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I123443094 |
| authorships[4].affiliations[0].raw_affiliation_string | Universidade Estadual de Maringá |
| authorships[4].institutions[0].id | https://openalex.org/I123443094 |
| authorships[4].institutions[0].ror | https://ror.org/04bqqa360 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I123443094 |
| authorships[4].institutions[0].country_code | BR |
| authorships[4].institutions[0].display_name | Universidade Estadual de Maringá |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Bruna Alves |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Universidade Estadual de Maringá |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.ajs.or.at/index.php/ajs/article/download/1407/786 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | A Flexible Probability Model for Proportion Data: Unit Gumbel Type-II Distribution, Development, Properties, Different Method of Estimations and Applications |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11918 |
| primary_topic.field.id | https://openalex.org/fields/18 |
| primary_topic.field.display_name | Decision Sciences |
| primary_topic.score | 0.9688000082969666 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1803 |
| primary_topic.subfield.display_name | Management Science and Operations Research |
| primary_topic.display_name | Forecasting Techniques and Applications |
| related_works | https://openalex.org/W2115040659, https://openalex.org/W3124023584, https://openalex.org/W2392757156, https://openalex.org/W3121924949, https://openalex.org/W4210771670, https://openalex.org/W2951988075, https://openalex.org/W2270643620, https://openalex.org/W1570428685, https://openalex.org/W2083778309, https://openalex.org/W4225649502 |
| cited_by_count | 28 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 8 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 19 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | doi:10.17713/ajs.v52i2.1407 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764411241 |
| best_oa_location.source.issn | 1026-597X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1026-597X |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Austrian Journal of Statistics |
| best_oa_location.source.host_organization | https://openalex.org/P4310317894 |
| best_oa_location.source.host_organization_name | Austrian Journal of Statistics |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310317894 |
| best_oa_location.source.host_organization_lineage_names | Austrian Journal of Statistics |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.ajs.or.at/index.php/ajs/article/download/1407/786 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Austrian Journal of Statistics |
| best_oa_location.landing_page_url | https://doi.org/10.17713/ajs.v52i2.1407 |
| primary_location.id | doi:10.17713/ajs.v52i2.1407 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764411241 |
| primary_location.source.issn | 1026-597X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1026-597X |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Austrian Journal of Statistics |
| primary_location.source.host_organization | https://openalex.org/P4310317894 |
| primary_location.source.host_organization_name | Austrian Journal of Statistics |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310317894 |
| primary_location.source.host_organization_lineage_names | Austrian Journal of Statistics |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.ajs.or.at/index.php/ajs/article/download/1407/786 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Austrian Journal of Statistics |
| primary_location.landing_page_url | https://doi.org/10.17713/ajs.v52i2.1407 |
| publication_date | 2023-03-12 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3135056216, https://openalex.org/W6650381011, https://openalex.org/W7071592772, https://openalex.org/W2008149271, https://openalex.org/W6607910233, https://openalex.org/W2598694153, https://openalex.org/W6634781086, https://openalex.org/W2094764829, https://openalex.org/W2113312317, https://openalex.org/W4283320625, https://openalex.org/W6791027796, https://openalex.org/W3153890396, https://openalex.org/W6765657330, https://openalex.org/W3135245197, https://openalex.org/W2743259293, https://openalex.org/W2971089215, https://openalex.org/W1989237447, https://openalex.org/W1982528061, https://openalex.org/W2592905339, https://openalex.org/W1978039195, https://openalex.org/W2582743722, https://openalex.org/W2496800853, https://openalex.org/W6668656008, https://openalex.org/W3094517763, https://openalex.org/W3113721704, https://openalex.org/W3102723784, https://openalex.org/W2808742638, https://openalex.org/W2006652113, https://openalex.org/W193160530, https://openalex.org/W4256068548, https://openalex.org/W4298927045, https://openalex.org/W1973429805, https://openalex.org/W4241763521, https://openalex.org/W2046262695, https://openalex.org/W4245913078, https://openalex.org/W1579369571, https://openalex.org/W2904177731, https://openalex.org/W3122896559, https://openalex.org/W2954461242, https://openalex.org/W2125697860, https://openalex.org/W2073911314 |
| referenced_works_count | 41 |
| abstract_inverted_index.In | 0, 26, 56, 141, 158 |
| abstract_inverted_index.It | 12 |
| abstract_inverted_index.We | 85 |
| abstract_inverted_index.as | 44, 118, 120 |
| abstract_inverted_index.in | 33, 59, 108, 132, 149 |
| abstract_inverted_index.is | 13, 127 |
| abstract_inverted_index.of | 28, 61, 81, 90, 95, 113, 125, 134 |
| abstract_inverted_index.on | 64 |
| abstract_inverted_index.or | 47 |
| abstract_inverted_index.to | 16, 110, 151, 160 |
| abstract_inverted_index.we | 37, 69 |
| abstract_inverted_index.The | 123 |
| abstract_inverted_index.and | 2, 35, 53, 71, 78, 137 |
| abstract_inverted_index.are | 9, 105 |
| abstract_inverted_index.few | 80 |
| abstract_inverted_index.for | 23, 40, 50, 116 |
| abstract_inverted_index.its | 82 |
| abstract_inverted_index.may | 38 |
| abstract_inverted_index.out | 107 |
| abstract_inverted_index.six | 162 |
| abstract_inverted_index.the | 18, 65, 73, 92, 99, 142, 153, 161 |
| abstract_inverted_index.two | 144 |
| abstract_inverted_index.also | 86 |
| abstract_inverted_index.been | 147 |
| abstract_inverted_index.best | 19 |
| abstract_inverted_index.bias | 136 |
| abstract_inverted_index.data | 42 |
| abstract_inverted_index.end, | 143 |
| abstract_inverted_index.from | 98 |
| abstract_inverted_index.have | 146 |
| abstract_inverted_index.life | 5 |
| abstract_inverted_index.like | 32 |
| abstract_inverted_index.mean | 138 |
| abstract_inverted_index.real | 4, 29 |
| abstract_inverted_index.this | 57 |
| abstract_inverted_index.unit | 74 |
| abstract_inverted_index.very | 10, 14 |
| abstract_inverted_index.view | 60 |
| abstract_inverted_index.well | 119 |
| abstract_inverted_index.(see, | 49 |
| abstract_inverted_index.Carlo | 103 |
| abstract_inverted_index.Monte | 102 |
| abstract_inverted_index.Olkin | 54 |
| abstract_inverted_index.data. | 25 |
| abstract_inverted_index.large | 121 |
| abstract_inverted_index.model | 97 |
| abstract_inverted_index.ofnew | 156 |
| abstract_inverted_index.order | 109 |
| abstract_inverted_index.small | 117 |
| abstract_inverted_index.study | 72 |
| abstract_inverted_index.terms | 133 |
| abstract_inverted_index.their | 135 |
| abstract_inverted_index.using | 129 |
| abstract_inverted_index.world | 30 |
| abstract_inverted_index.Gumbel | 66, 75 |
| abstract_inverted_index.UG-TII | 96 |
| abstract_inverted_index.error. | 140 |
| abstract_inverted_index.model, | 68 |
| abstract_inverted_index.model. | 157 |
| abstract_inverted_index.select | 17 |
| abstract_inverted_index.severe | 163 |
| abstract_inverted_index.square | 139 |
| abstract_inverted_index.worked | 106 |
| abstract_inverted_index.Type-II | 67, 76 |
| abstract_inverted_index.attempt | 150 |
| abstract_inverted_index.bounded | 41 |
| abstract_inverted_index.compare | 111 |
| abstract_inverted_index.explore | 79 |
| abstract_inverted_index.fitting | 20 |
| abstract_inverted_index.methods | 89, 115 |
| abstract_inverted_index.samples | 131 |
| abstract_inverted_index.suggest | 70 |
| abstract_inverted_index.unknown | 93 |
| abstract_inverted_index.various | 88 |
| abstract_inverted_index.(2007)). | 55 |
| abstract_inverted_index.Marshall | 52 |
| abstract_inverted_index.analysis | 27 |
| abstract_inverted_index.consider | 87 |
| abstract_inverted_index.context, | 58 |
| abstract_inverted_index.datasets | 145 |
| abstract_inverted_index.examined | 148 |
| abstract_inverted_index.example, | 51 |
| abstract_inverted_index.helpful. | 11 |
| abstract_inverted_index.measured | 128 |
| abstract_inverted_index.observed | 43 |
| abstract_inverted_index.samples. | 122 |
| abstract_inverted_index.validate | 152 |
| abstract_inverted_index.fractions | 48 |
| abstract_inverted_index.important | 15 |
| abstract_inverted_index.modelling | 24 |
| abstract_inverted_index.pertinent | 62 |
| abstract_inverted_index.phenomena | 31 |
| abstract_inverted_index.realistic | 154 |
| abstract_inverted_index.simulated | 130 |
| abstract_inverted_index.comparison | 159 |
| abstract_inverted_index.economics, | 36 |
| abstract_inverted_index.efficiency | 112, 124 |
| abstract_inverted_index.estimating | 91 |
| abstract_inverted_index.estimators | 126 |
| abstract_inverted_index.explaining | 1 |
| abstract_inverted_index.parameters | 94 |
| abstract_inverted_index.scenarios, | 6 |
| abstract_inverted_index.forecasting | 3 |
| abstract_inverted_index.frequentist | 100 |
| abstract_inverted_index.proportions | 46 |
| abstract_inverted_index.reliability | 34 |
| abstract_inverted_index.simulations | 104 |
| abstract_inverted_index.statistical | 7, 21, 83 |
| abstract_inverted_index.competitors. | 164 |
| abstract_inverted_index.distribution | 22 |
| abstract_inverted_index.percentages, | 45 |
| abstract_inverted_index.perspective. | 101 |
| abstract_inverted_index.(UG-TII)model | 77 |
| abstract_inverted_index.distributions | 8 |
| abstract_inverted_index.possibilities | 155 |
| abstract_inverted_index.transformation | 63 |
| abstract_inverted_index.characteristics. | 84 |
| abstract_inverted_index.finddistributions | 39 |
| abstract_inverted_index.suggestedestimation | 114 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/8 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Decent work and economic growth |
| citation_normalized_percentile.value | 0.9767243 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |