{"id":"https://openalex.org/W3137565064","doi":null,"title":"Regression Analysis of Research Data using R Programming","display_name":"Regression Analysis of Research Data using R Programming","publication_year":2019,"publication_date":"2019-09-03","ids":{"openalex":"https://openalex.org/W3137565064","mag":"3137565064"},"language":"en","primary_location":{"id":"mag:3137565064","doi":null,"is_oa":false,"landing_page_url":"http://computers.stmjournals.com/index.php?journal=RTPL&page=article&op=view&path%5B%5D=2236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004490167","display_name":"Yagyanath Rimal","orcid":"https://orcid.org/0000-0003-1045-7728","observed_orcids":["https://orcid.org/0000-0003-1045-7728"]},"institutions":[{"id":"https://openalex.org/I151104398","display_name":"Pokhara University","ror":"https://ror.org/02dayf324","country_code":"NP","type":"education","lineage":["https://openalex.org/I151104398"]}],"countries":["NP"],"is_corresponding":true,"raw_author_name":"Yagyanath Rimal","raw_affiliation_strings":["Pokhara University, Lekhnath"],"raw_orcid":"https://orcid.org/0000-0003-1045-7728","affiliations":[{"raw_affiliation_string":"Pokhara University, Lekhnath","institution_ids":["https://openalex.org/I151104398"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004490167"],"corresponding_institution_ids":["https://openalex.org/I151104398"],"apc_list":null,"apc_paid":null,"fwci":0.1731,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58254972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"6","issue":"2","first_page":"42","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.9218999743461609,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.9218999743461609,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13141","display_name":"Statistical Methods and Applications","score":0.061400000005960464,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.014000000432133675,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regression-analysis","display_name":"regression analysis","score":0.9909999966621399},{"id":"https://openalex.org/keywords/r-programming","display_name":"R programming language","score":0.8560000061988831},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.996999979019165},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.9760000109672546},{"id":"https://openalex.org/keywords/quantile-regression","display_name":"quantile regression","score":1.0},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"polynomial regression","score":0.9980000257492065},{"id":"https://openalex.org/keywords/data-analysis","display_name":"data analysis","score":0.5249999761581421},{"id":"https://openalex.org/keywords/big-data","display_name":"big data","score":0.628000020980835}],"concepts":[{"id":"https://openalex.org/C63817138","wikidata":"https://www.wikidata.org/wiki/Q3455889","display_name":"Quantile regression","level":2,"score":0.7705224752426147},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6474366784095764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6314209699630737},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5423049330711365},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.5191028118133545},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4552520513534546},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.43034467101097107},{"id":"https://openalex.org/C57381214","wikidata":"https://www.wikidata.org/wiki/Q55631393","display_name":"Regression diagnostic","level":4,"score":0.4295574426651001},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.42940133810043335},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.41497525572776794},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37286531925201416},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3258039057254791},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24064388871192932},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21612221002578735},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.194413959980011}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3137565064","doi":null,"is_oa":false,"landing_page_url":"http://computers.stmjournals.com/index.php?journal=RTPL&page=article&op=view&path%5B%5D=2236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7219873211","https://openalex.org/W4322755541","https://openalex.org/W1640771061","https://openalex.org/W2941851500","https://openalex.org/W7135868976","https://openalex.org/W4309024687","https://openalex.org/W2772928180","https://openalex.org/W7002321560","https://openalex.org/W7216965119","https://openalex.org/W7045208486"],"abstract_inverted_index":{"ABSTRACT":[0],"The":[3,27],"goal":[4],"of":[5,16,30,38,61,70,97],"the":[6,11,36,58],"review":[7],"paper":[8,32,56],"is":[9,33],"discussing":[10],"relationship":[12,37],"between":[13],"various":[14],"types":[15],"regression":[17,44,62],"analysis":[18,63],"whose":[19],"output":[20],"was":[21],"sufficiently":[22],"analyzed":[23],"using":[24,100],"R":[25,66,101],"programming.":[26],"primary":[28],"purpose":[29],"this":[31,55,89],"to":[34,46],"explain":[35],"linear,":[39],"multiple,":[40],"quantile":[41],"and":[42,65],"polynomial":[43],"models":[45],"achieve":[47],"final":[48],"conclusion":[49],"with":[50],"different":[51],"data":[52,71],"sets.":[53],"Therefore,":[54],"presents":[57],"easiest":[59],"way":[60],"commands":[64],"programming":[67],"strengths":[68],"for":[69],"analysis.\u00a0":[72],"Keyword:":[75],"\u00a0Data":[77],"Analytics;":[78],"Linear,":[79],"Quantile,":[80],"Polynomial,":[81],"Big":[82],"Data;":[83],"Regression":[84,95],"Equation.":[85],"Cite":[88],"Article":[90],"Yagyanath":[93],"Rimal.":[94],"Analysis":[96],"Research":[98],"Data":[99],"Programming":[102,110],".":[103],"Recent":[107],"Trends":[108],"in":[109],"Languages.":[111],"2019;":[112],"6(2):":[113],"42\u201350p.":[114]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T04:12:42.849631","created_date":"2021-03-29T00:00:00"}