Publication Information

{'id': 'https://openalex.org/W2350937080', 'doi': None, 'title': 'Narration on Regression Analysis Methods Applied in Environmental Fields', 'display_name': 'Narration on Regression Analysis Methods Applied in Environmental Fields', 'publication_year': 2008, 'publication_date': '2008-01-01', 'ids': {'openalex': 'https://openalex.org/W2350937080', 'mag': '2350937080'}, 'language': 'en', 'primary_location': {'is_oa': False, 'landing_page_url': 'http://en.cnki.com.cn/Article_en/CJFDTOTAL-JSHJ2008S2016.htm', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S13479253', 'display_name': 'Environmental Science & Technology', 'issn_l': '0013-936X', 'issn': ['0013-936X', '1520-5851'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320006', 'host_organization_name': 'American Chemical Society', 'host_organization_lineage': ['https://openalex.org/P4310320006'], 'host_organization_lineage_names': ['American Chemical Society'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}, 'type': 'article', 'type_crossref': 'journal-article', 'indexed_in': [], '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/A5049637184', 'display_name': 'Wang Jiang-pin', 'orcid': None}, 'institutions': [], 'countries': [], 'is_corresponding': True, 'raw_author_name': 'Wang Jiang-pin', 'raw_affiliation_strings': [], 'affiliations': []}], 'institution_assertions': [], 'countries_distinct_count': 0, 'institutions_distinct_count': 0, 'corresponding_author_ids': ['https://openalex.org/A5049637184'], 'corresponding_institution_ids': [], 'apc_list': None, 'apc_paid': None, 'fwci': 0.0, 'has_fulltext': False, 'cited_by_count': 2, 'citation_normalized_percentile': {'value': 0.798376, 'is_in_top_1_percent': False, 'is_in_top_10_percent': False}, 'cited_by_percentile_year': {'min': 70, 'max': 74}, 'biblio': {'volume': None, 'issue': None, 'first_page': None, 'last_page': None}, 'is_retracted': False, 'is_paratext': False, 'primary_topic': {'id': 'https://openalex.org/T13535', 'display_name': 'Wireless Sensor Networks and IoT', 'score': 0.1463, 'subfield': {'id': 'https://openalex.org/subfields/2207', 'display_name': 'Control and Systems 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/T13535', 'display_name': 'Wireless Sensor Networks and IoT', 'score': 0.1463, 'subfield': {'id': 'https://openalex.org/subfields/2207', 'display_name': 'Control and Systems 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/T13890', 'display_name': 'Remote Sensing and Land Use', 'score': 0.1455, 'subfield': {'id': 'https://openalex.org/subfields/1902', 'display_name': 'Atmospheric Science'}, 'field': {'id': 'https://openalex.org/fields/19', 'display_name': 'Earth and Planetary Sciences'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}, {'id': 'https://openalex.org/T13734', 'display_name': 'Advanced Computational Techniques and Applications', 'score': 0.1387, 'subfield': {'id': 'https://openalex.org/subfields/1702', 'display_name': 'Artificial Intelligence'}, 'field': {'id': 'https://openalex.org/fields/17', 'display_name': 'Computer Science'}, 'domain': {'id': 'https://openalex.org/domains/3', 'display_name': 'Physical Sciences'}}], 'keywords': [{'id': 'https://openalex.org/keywords/regression-diagnostic', 'display_name': 'Regression diagnostic', 'score': 0.7013746}, {'id': 'https://openalex.org/keywords/statistic', 'display_name': 'Statistic', 'score': 0.5377953}, {'id': 'https://openalex.org/keywords/factor-regression-model', 'display_name': 'Factor regression model', 'score': 0.4120248}], 'concepts': [{'id': 'https://openalex.org/C152877465', 'wikidata': 'https://www.wikidata.org/wiki/Q208042', 'display_name': 'Regression analysis', 'level': 2, 'score': 0.7493565}, {'id': 'https://openalex.org/C57381214', 'wikidata': 'https://www.wikidata.org/wiki/Q55631393', 'display_name': 'Regression diagnostic', 'level': 4, 'score': 0.7013746}, {'id': 'https://openalex.org/C32224588', 'wikidata': 'https://www.wikidata.org/wiki/Q7250175', 'display_name': 'Proper linear model', 'level': 4, 'score': 0.66658473}, {'id': 'https://openalex.org/C83546350', 'wikidata': 'https://www.wikidata.org/wiki/Q1139051', 'display_name': 'Regression', 'level': 2, 'score': 0.5896324}, {'id': 'https://openalex.org/C105795698', 'wikidata': 'https://www.wikidata.org/wiki/Q12483', 'display_name': 'Statistics', 'level': 1, 'score': 0.56679165}, {'id': 'https://openalex.org/C48921125', 'wikidata': 'https://www.wikidata.org/wiki/Q10861030', 'display_name': 'Linear regression', 'level': 2, 'score': 0.5645083}, {'id': 'https://openalex.org/C89128539', 'wikidata': 'https://www.wikidata.org/wiki/Q1949963', 'display_name': 'Statistic', 'level': 2, 'score': 0.5377953}, {'id': 'https://openalex.org/C90157343', 'wikidata': 'https://www.wikidata.org/wiki/Q5188196', 'display_name': 'Cross-sectional regression', 'level': 4, 'score': 0.51182073}, {'id': 'https://openalex.org/C35519122', 'wikidata': 'https://www.wikidata.org/wiki/Q3775699', 'display_name': 'Segmented regression', 'level': 4, 'score': 0.46343216}, {'id': 'https://openalex.org/C120068334', 'wikidata': 'https://www.wikidata.org/wiki/Q45343', 'display_name': 'Polynomial regression', 'level': 3, 'score': 0.4591841}, {'id': 'https://openalex.org/C64946054', 'wikidata': 'https://www.wikidata.org/wiki/Q4874476', 'display_name': 'Bayesian multivariate linear regression', 'level': 3, 'score': 0.41532236}, {'id': 'https://openalex.org/C93698799', 'wikidata': 'https://www.wikidata.org/wiki/Q5428730', 'display_name': 'Factor regression model', 'level': 5, 'score': 0.4120248}, {'id': 'https://openalex.org/C149782125', 'wikidata': 'https://www.wikidata.org/wiki/Q160039', 'display_name': 'Econometrics', 'level': 1, 'score': 0.3896019}, {'id': 'https://openalex.org/C33923547', 'wikidata': 'https://www.wikidata.org/wiki/Q395', 'display_name': 'Mathematics', 'level': 0, 'score': 0.36135465}, {'id': 'https://openalex.org/C41008148', 'wikidata': 'https://www.wikidata.org/wiki/Q21198', 'display_name': 'Computer science', 'level': 0, 'score': 0.35741025}], 'mesh': [], 'locations_count': 1, 'locations': [{'is_oa': False, 'landing_page_url': 'http://en.cnki.com.cn/Article_en/CJFDTOTAL-JSHJ2008S2016.htm', 'pdf_url': None, 'source': {'id': 'https://openalex.org/S13479253', 'display_name': 'Environmental Science & Technology', 'issn_l': '0013-936X', 'issn': ['0013-936X', '1520-5851'], 'is_oa': False, 'is_in_doaj': False, 'is_core': True, 'host_organization': 'https://openalex.org/P4310320006', 'host_organization_name': 'American Chemical Society', 'host_organization_lineage': ['https://openalex.org/P4310320006'], 'host_organization_lineage_names': ['American Chemical Society'], 'type': 'journal'}, 'license': None, 'license_id': None, 'version': None, 'is_accepted': False, 'is_published': False}], 'best_oa_location': None, 'sustainable_development_goals': [], 'grants': [], 'datasets': [], 'versions': [], 'referenced_works_count': 0, 'referenced_works': [], 'related_works': ['https://openalex.org/W64922074', 'https://openalex.org/W603221366', 'https://openalex.org/W57379937', 'https://openalex.org/W3175130226', 'https://openalex.org/W3148095850', 'https://openalex.org/W3087894613', 'https://openalex.org/W3023315192', 'https://openalex.org/W3000391549', 'https://openalex.org/W2936596189', 'https://openalex.org/W2772903726', 'https://openalex.org/W2729038047', 'https://openalex.org/W2385045799', 'https://openalex.org/W2378238046', 'https://openalex.org/W2374894797', 'https://openalex.org/W2371948165', 'https://openalex.org/W2316664010', 'https://openalex.org/W2288668272', 'https://openalex.org/W2279792316', 'https://openalex.org/W2069789390', 'https://openalex.org/W2040223003'], 'abstract_inverted_index': {'Regression': [0], 'analysis': [1, 20, 39, 80, 92], 'is': [2, 10, 85], 'a': [3], 'kind': [4], 'of': [5, 16, 59, 70, 78, 90], 'mathematics': [6], 'statistic': [7], 'method': [8], 'which': [9], 'used': [11], 'to': [12, 33], 'deal': [13], 'with': [14], 'correlations': [15], 'variable': [17], 'factors.Recently,': [18], 'regression': [19, 38, 62, 79, 91], 'model': [21], 'has': [22, 30], 'been': [23, 31], 'applied': [24], 'in': [25, 64, 81, 87, 93], 'many': [26, 94], 'environmental': [27, 65, 95], 'fields': [28], 'and': [29, 36, 50, 57, 73, 97], 'proved': [32], 'be': [34], 'correct': [35], 'doable.Basic': [37], 'methods': [40, 63], 'include': [41], 'unitary': [42], 'linear': [43, 46], 'regression,': [44, 47, 49], 'multiple': [45], 'stepwise': [48], 'so': [51], 'on.This': [52], 'article': [53], 'discussed': [54], 'the': [55, 68, 71, 75, 82], 'principle': [56], 'application': [58, 89], 'these': [60], 'basic': [61], 'science,': [66], 'dissertated': [67], 'effect': [69], 'application,': [72], 'predicted': [74], 'development': [76], 'trend': [77], 'future.This': [83], 'study': [84], 'valuable': [86], 'better': [88], 'science': [96], 'engineering': [98], 'fields.': [99]}, 'cited_by_api_url': 'https://api.openalex.org/works?filter=cites:W2350937080', 'counts_by_year': [{'year': 2018, 'cited_by_count': 1}, {'year': 2015, 'cited_by_count': 1}], 'updated_date': '2024-12-13T06:31:31.399866', 'created_date': '2016-06-24'}