Get quick answers to your questions about the article from our AI researcher chatbot
{'id': 'https://openalex.org/W2983015804', 'doi': 'https://doi.org/10.1002/env.2607', 'title': 'Goodness‐of‐fit tests for<i><b>β</b></i>ARMA hydrological time series modeling', 'display_name': 'Goodness‐of‐fit tests for<i><b>β</b></i>ARMA hydrological time series modeling', 'publication_year': 2019, 'publication_date': '2019-11-14', 'ids': {'openalex': 'https://openalex.org/W2983015804', 'doi': 'https://doi.org/10.1002/env.2607', 'mag': '2983015804'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'https://doi.org/10.1002/env.2607', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S17114410', 'display_name': 'Environmetrics', 'issn_l': '1099-095X', 'issn': ['1099-095X', '1180-4009'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320595', 'host_organization_name': 'Wiley', 'host_organization_lineage': ['https://openalex.org/P4310320595'], 'host_organization_lineage_names': ['Wiley'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': ['crossref'], 'open_access': {'is_oa': False, 'oa_status': 'closed', 'oa_url': None, 'any_repository_has_fulltext': False}, 'authorships': [{'author_position': 'first', 'author': {'id': 'https://openalex.org/A5038961762', 'display_name': 'Vinícius Teodoro Scher', 'orcid': 'https://orcid.org/0000-0003-0406-0265'}, 'institutions': [{'id': 'https://openalex.org/I25112270', 'display_name': 'Universidade Federal de Pernambuco', 'ror': 'https://ror.org/047908t24', 'country_code': 'BR', 'type': 'education', 'lineage': ['https://openalex.org/I25112270']}], 'countries': ['BR'], 'is_corresponding': False, 'raw_author_name': 'Vinícius T. Scher', 'raw_affiliation_strings': ['Departamento de Estatística Universidade Federal de Pernambuco Recife Brazil'], 'affiliations': [{'raw_affiliation_string': 'Departamento de Estatística Universidade Federal de Pernambuco Recife Brazil', 'institution_ids': ['https://openalex.org/I25112270']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5022676431', 'display_name': 'Francisco Cribari‐Neto', 'orcid': 'https://orcid.org/0000-0002-5909-6698'}, 'institutions': [{'id': 'https://openalex.org/I25112270', 'display_name': 'Universidade Federal de Pernambuco', 'ror': 'https://ror.org/047908t24', 'country_code': 'BR', 'type': 'education', 'lineage': ['https://openalex.org/I25112270']}], 'countries': ['BR'], 'is_corresponding': True, 'raw_author_name': 'Francisco Cribari‐Neto', 'raw_affiliation_strings': ['Departamento de Estatística Universidade Federal de Pernambuco Recife Brazil'], 'affiliations': [{'raw_affiliation_string': 'Departamento de Estatística Universidade Federal de Pernambuco Recife Brazil', 'institution_ids': ['https://openalex.org/I25112270']}]}, {'author_position': 'middle', 'author': {'id': 'https://openalex.org/A5082339253', 'display_name': 'Guilherme Pumi', 'orcid': 'https://orcid.org/0000-0002-6256-3170'}, 'institutions': [{'id': 'https://openalex.org/I130442723', 'display_name': 'Universidade Federal do Rio Grande do Sul', 'ror': 'https://ror.org/041yk2d64', 'country_code': 'BR', 'type': 'education', 'lineage': ['https://openalex.org/I130442723']}], 'countries': ['BR'], 'is_corresponding': False, 'raw_author_name': 'Guilherme Pumi', 'raw_affiliation_strings': ['Departamento de Estatística Universidade Federal do Rio Grande do Sul Porto Alegre Brazil'], 'affiliations': [{'raw_affiliation_string': 'Departamento de Estatística Universidade Federal do Rio Grande do Sul Porto Alegre Brazil', 'institution_ids': ['https://openalex.org/I130442723']}]}, {'author_position': 'last', 'author': {'id': 'https://openalex.org/A5037356875', 'display_name': 'Fábio M. Bayer', 'orcid': 'https://orcid.org/0000-0002-1464-0805'}, 'institutions': [{'id': 'https://openalex.org/I33501960', 'display_name': 'Universidade Federal de Santa Maria', 'ror': 'https://ror.org/01b78mz79', 'country_code': 'BR', 'type': 'education', 'lineage': ['https://openalex.org/I33501960']}], 'countries': ['BR'], 'is_corresponding': False, 'raw_author_name': 'Fábio M. Bayer', 'raw_affiliation_strings': ['Departamento de Estatística Universidade Federal de Santa Maria Santa Maria Brazil'], 'affiliations': [{'raw_affiliation_string': 'Departamento de Estatística Universidade Federal de Santa Maria Santa Maria Brazil', 'institution_ids': ['https://openalex.org/I33501960']}]}], 'institution_assertions': [], 'countries_distinct_count': 1, 'institutions_distinct_count': 3, 'corresponding_author_ids': ['https://openalex.org/A5022676431'], 'corresponding_institution_ids': ['https://openalex.org/I25112270'], 'apc_list': {'value': 4330, 'currency': 'USD', 'value_usd': 4330, 'provenance': 'doaj'}, 'apc_paid': None, 'fwci': 1.923, 'has_fulltext': False, 'cited_by_count': 20, 'citation_normalized_percentile': {'value': 0.905505, 'is_in_top_1_percent': False, 'is_in_top_10_percent': True}, 'cited_by_percentile_year': {'min': 91, 'max': 92}, 'biblio': {'volume': '31', 'issue': '3', 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T10969', 'display_name': 'Water resources management and optimization', 'score': 0.9897, 'subfield': {'id': 'https://openalex.org/subfields/2212', 'display_name': 'Ocean Engineering'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, 'topics': [{'id': 'https://openalex.org/T10969', 'display_name': 'Water resources management and optimization', 'score': 0.9897, 'subfield': {'id': 'https://openalex.org/subfields/2212', 'display_name': 'Ocean Engineering'}, 'field': {'id': 'https://openalex.org/fields/22', 'display_name': 'Engineering'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T11186', 'display_name': 'Hydrology and Drought Analysis', 'score': 0.9889, 'subfield': {'id': 'https://openalex.org/subfields/2306', 'display_name': 'Global and Planetary Change'}, 'field': {'id': 'https://openalex.org/fields/23', 'display_name': 'Environmental Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T11059', 'display_name': 'Market Dynamics and Volatility', 'score': 0.9877, 'subfield': {'id': 'https://openalex.org/subfields/2002', 'display_name': 'Economics and Econometrics'}, 'field': {'id': 'https://openalex.org/fields/20', 'display_name': 'Economics, Econometrics and Finance'}, 'domain': {'id': 'https://openalex.org/domains/2', 'display_name': 'Social Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/autoregressive–moving-average-model', 'display_name': 'Autoregressive–moving-average model', 'score': 0.6598604}, {'id': 'https://openalex.org/keywords/goodness-of-fit', 'display_name': 'Goodness of fit', 'score': 0.5408448}, {'id': 'https://openalex.org/keywords/moving-average', 'display_name': 'Moving average', 'score': 0.44151852}], 'concepts': [{'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.6912831}, {'id': 'https://openalex.org/C74883015', 'wikidata': 'https://www.wikidata.org/wiki/Q290467', 'display_name': 'Autoregressive–moving-average model', 'level': 3, 'score': 0.6598604}, {'id': 'https://openalex.org/C105795698', 'wikidata': 'https://www.wikidata.org/wiki/Q12483', 'display_name': 'Statistics', 'level': 1, 'score': 0.5415128}, {'id': 'https://openalex.org/C132480984', 'wikidata': 'https://www.wikidata.org/wiki/Q2034239', 'display_name': 'Goodness of fit', 'level': 2, 'score': 0.5408448}, {'id': 'https://openalex.org/C143724316', 'wikidata': 'https://www.wikidata.org/wiki/Q312468', 'display_name': 'Series (stratigraphy)', 'level': 2, 'score': 0.52988964}, {'id': 'https://openalex.org/C159877910', 'wikidata': 'https://www.wikidata.org/wiki/Q2202883', 'display_name': 'Autoregressive model', 'level': 2, 'score': 0.5237051}, {'id': 'https://openalex.org/C28826006', 'wikidata': 'https://www.wikidata.org/wiki/Q33521', 'display_name': 'Applied mathematics', 'level': 1, 'score': 0.46890938}, {'id': 'https://openalex.org/C169857963', 'wikidata': 'https://www.wikidata.org/wiki/Q1461038', 'display_name': 'Test statistic', 'level': 3, 'score': 0.45533696}, {'id': 'https://openalex.org/C175706884', 'wikidata': 'https://www.wikidata.org/wiki/Q1130194', 'display_name': 'Moving average', 'level': 2, 'score': 0.44151852}, {'id': 'https://openalex.org/C87007009', 'wikidata': 'https://www.wikidata.org/wiki/Q210832', 'display_name': 'Statistical hypothesis testing', 'level': 2, 'score': 0.42065236}, {'id': 'https://openalex.org/C149782125', 'wikidata': 'https://www.wikidata.org/wiki/Q160039', 'display_name': 'Econometrics', 'level': 1, 'score': 0.34414098}, {'id': 'https://openalex.org/C151730666', 'wikidata': 'https://www.wikidata.org/wiki/Q7205', 'display_name': 'Paleontology', 'level': 1, 'score': 0.0}, {'id': 'https://openalex.org/C86803240', 'wikidata': 'https://www.wikidata.org/wiki/Q420', 'display_name': 'Biology', 'level': 0, 'score': 0.0}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'https://doi.org/10.1002/env.2607', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S17114410', 'display_name': 'Environmetrics', 'issn_l': '1099-095X', 'issn': ['1099-095X', '1180-4009'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320595', 'host_organization_name': 'Wiley', 'host_organization_lineage': ['https://openalex.org/P4310320595'], 'host_organization_lineage_names': ['Wiley'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [], 'grants': [{'funder': 'https://openalex.org/F4320322025', 'funder_display_name': 'Conselho Nacional de Desenvolvimento Científico e Tecnológico', 'award_id': '305350/2017-0'}, {'funder': 'https://openalex.org/F4320322025', 'funder_display_name': 'Conselho Nacional de Desenvolvimento Científico e Tecnológico', 'award_id': '301651/2017-5'}], 'datasets': [], 'versions': [], 'referenced_works_count': 44, 'referenced_works': ['https://openalex.org/W1774309483', 'https://openalex.org/W1965792011', 'https://openalex.org/W1967859109', 'https://openalex.org/W1971601353', 'https://openalex.org/W1994811096', 'https://openalex.org/W1998643818', 'https://openalex.org/W2009632219', 'https://openalex.org/W2040992239', 'https://openalex.org/W2043589064', 'https://openalex.org/W2056251361', 'https://openalex.org/W2073698874', 'https://openalex.org/W2080801582', 'https://openalex.org/W2082036952', 'https://openalex.org/W2083670032', 'https://openalex.org/W2087368810', 'https://openalex.org/W2093230975', 'https://openalex.org/W2095595785', 'https://openalex.org/W2102856220', 'https://openalex.org/W2111940674', 'https://openalex.org/W2117450242', 'https://openalex.org/W2123971949', 'https://openalex.org/W2142635246', 'https://openalex.org/W2142792039', 'https://openalex.org/W2160141294', 'https://openalex.org/W2394808709', 'https://openalex.org/W2568630534', 'https://openalex.org/W2582743722', 'https://openalex.org/W2591764123', 'https://openalex.org/W2593817800', 'https://openalex.org/W2605221469', 'https://openalex.org/W2761410942', 'https://openalex.org/W2808920857', 'https://openalex.org/W2883812008', 'https://openalex.org/W2904302135', 'https://openalex.org/W2905060314', 'https://openalex.org/W2963513064', 'https://openalex.org/W3104121267', 'https://openalex.org/W3122820950', 'https://openalex.org/W404240460', 'https://openalex.org/W4210829820', 'https://openalex.org/W4246587917', 'https://openalex.org/W4256110495', 'https://openalex.org/W4372144402', 'https://openalex.org/W73885982'], 'related_works': ['https://openalex.org/W905014826', 'https://openalex.org/W3190289737', 'https://openalex.org/W307809402', 'https://openalex.org/W3015822731', 'https://openalex.org/W2413726729', 'https://openalex.org/W2384744720', 'https://openalex.org/W2367697829', 'https://openalex.org/W2036994430', 'https://openalex.org/W1985666753', 'https://openalex.org/W1600093848'], 'abstract_inverted_index': {'Abstract': [0], 'We': [1, 68, 87, 162], 'address': [2], 'the': [3, 18, 26, 31, 38, 46, 63, 89, 94, 105, 120, 136, 144, 153, 169, 173, 191, 213, 223, 226, 238], 'issue': [4], 'of': [5, 30, 33, 40, 48, 65, 93, 139, 146, 172, 225, 228], 'performing': [6], 'portmanteau': [7, 141, 175], 'testing': [8, 71], 'inference': [9], 'using': [10], 'time': [11, 27, 79, 112], 'series': [12, 28, 80, 113], 'data': [13], 'that': [14, 73, 132, 150, 190, 237], 'assume': [15], 'values': [16], 'in': [17, 37, 45, 99, 143, 232], 'standard': [19, 140], 'unit': [20], 'interval.': [21], 'The': [22, 184, 234], 'motivation': [23], 'involves': [24], 'modeling': [25], 'dynamics': [29, 224], 'proportion': [32, 227], 'stocked': [34, 229], 'hydroelectric': [35, 230], 'energy': [36, 231], 'South': [39], 'Brazil.': [41, 233], 'Our': [42], 'focus': [43], 'lies': [44], 'class': [47, 145], 'beta': [49], 'autoregressive': [50], 'moving': [51], 'average': [52], '(': [53], 'β': [54, 125, 147, 181, 239], 'ARMA)': [55], 'models.': [56, 67, 183], 'In': [57], 'particular,': [58], 'we': [59, 187, 215, 221], 'wish': [60], 'to': [61, 109, 119, 158, 167], 'test': [62, 97, 160, 201, 203], 'goodness‐of‐fit': [64], 'such': [66], 'consider': [69], 'several': [70], 'criteria': [72], 'have': [74], 'been': [75], 'proposed': [76, 96], 'for': [77], 'Gaussian': [78], 'models': [81, 149, 245], 'and': [82, 114, 246], 'introduce': [83], 'two': [84, 95, 100], 'new': [85, 192], 'tests.': [86], 'derive': [88], 'asymptotic': [90, 137], 'null': [91, 154], 'distribution': [92], 'statistics': [98], 'different': [101, 174], 'scenarios,': [102], 'namely,': [103], 'when': [104, 115, 177], 'tests': [106, 142, 176, 193, 214], 'are': [107, 117, 194], 'applied': [108, 118], 'an': [110, 247], 'observed': [111], 'they': [116], 'residuals': [121], 'from': [122], 'a': [123, 199], 'fitted': [124, 180], 'ARMA': [126, 148, 182, 240], 'model.': [127], 'It': [128], 'is': [129, 205], 'worth': [130], 'noticing': [131], 'our': [133, 159], 'results': [134, 186, 235], 'imply': [135], 'validity': [138], 'are,': [151], 'under': [152], 'hypothesis,': [155], 'asymptotically': [156], 'equivalent': [157], 'statistics.': [161], 'use': [163], 'Monte': [164], 'Carlo': [165], 'simulation': [166, 185], 'assess': [168], 'relative': [170], 'merits': [171], 'used': [178], 'with': [179], 'present': [188], 'show': [189, 236], 'typically': [195], 'more': [196], 'powerful': [197], 'than': [198], 'well‐known': [200], 'whose': [202], 'statistic': [204], 'also': [206], 'based': [207], 'on': [208], 'residual': [209], 'partial': [210], 'autocorrelations.': [211], 'Overall,': [212], 'propose': [216], 'perform': [217], 'quite': [218], 'well.': [219], 'Finally,': [220], 'model': [222, 241], 'outperforms': [242], 'three': [243], 'alternative': [244], 'exponential': [248], 'smoothing': [249], 'algorithm.': [250]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2983015804', 'counts_by_year': [{'year': 2024, 'cited_by_count': 4}, {'year': 2023, 'cited_by_count': 6}, {'year': 2022, 'cited_by_count': 3}, {'year': 2021, 'cited_by_count': 4}, {'year': 2020, 'cited_by_count': 2}, {'year': 2019, 'cited_by_count': 1}], 'updated_date': '2025-01-15T19:43:08.578650', 'created_date': '2019-11-22'}