Prediction of cumulative egg production in japanese quails by using linear regression, linear piecewise regression and MARS algorithm

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dc.authoridALTAY, Yasin/0000-0003-4049-8301
dc.contributor.authorOzgur, Koskan
dc.contributor.authorYasin, Altay
dc.contributor.authorSedat, Aktan
dc.date.accessioned2025-01-21T16:33:06Z
dc.date.available2025-01-21T16:33:06Z
dc.date.issued2022
dc.departmentKırıkkale Üniversitesi
dc.description2nd International Applied Statistics Conference -- JUN 29-JUL 02, 2021 -- Tokat, TURKEY
dc.description.abstractThe study aims to predict the cumulative egg production of Japanese quails' by using linear regression, linear piecewise regression, and multivariate adaptive regression splines algorithms including age at sexual maturity, weight at sexual maturity, average weight of the first ten eggs, and partial-egg records (20, 30, 40, 60, 80, 100, and 150 d partial-egg records). All the raw data were acquired from a total of 128 female quails. To compare prediction methods, the fit criterions of 15 different models were examined, moreover the models were compared with the most common criterions. All prediction methods showed similar results, when the 40, 60, and 80 d partial-egg records included as independent variables in the models. Although the linear regression and the MARS algorithms inferred satisfying performance with 100 and 150 d of partial-egg records, the linear piecewise regression models gave a worse prophesying performance than others did. In conclusion, as an early (indirect) selection criterion, partial-egg records from d 100 can be successfully included as independent variable into the linear regression and MARS models to predict cumulative egg production.
dc.identifier.endpage99
dc.identifier.issn1124-4593
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85142533888
dc.identifier.scopusqualityQ3
dc.identifier.startpage93
dc.identifier.urihttps://hdl.handle.net/20.500.12587/23720
dc.identifier.volume28
dc.identifier.wosWOS:000952013600006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSivar-Soc Italiana Veterinari Animali Reddito
dc.relation.ispartofLarge Animal Review
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241229
dc.subjectEgg production; Partial egg record; Linear regression; Piecewise linear regression; MARS
dc.titlePrediction of cumulative egg production in japanese quails by using linear regression, linear piecewise regression and MARS algorithm
dc.typeConference Object

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