KRISHI
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/42600
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Neeraj Budhlakoti | en_US |
dc.contributor.author | Anil Rai | en_US |
dc.contributor.author | Dwijesh Chandra Mishra | en_US |
dc.date.accessioned | 2020-11-24T06:12:16Z | - |
dc.date.available | 2020-11-24T06:12:16Z | - |
dc.date.issued | 2020-05-21 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/42600 | - |
dc.description | Not Available | en_US |
dc.description.abstract | It is expected the predictive performance of genomic prediction methods may be adversely affected in the presence of outliers. In agriculture science an outlier may arise due to wrong data imputation, outlying response, and in a series of trials over the time or location. Although several statistical procedures are already there in literature for identification of outlier but identification of true outlier is still a challenge especially in case of high dimensional genomic data. Here we have proposed an efficient approach for detecting outlier in high dimensional genomic data, our approach is p-value based combination methods to produce single p-value for detecting the outliers. Robustness of our approach has been tested using simulated data through the evaluation measures like precision, recall etc. It has been observed that significant improvement in the performance of genomic prediction has been obtained by detecting the outliers and handling them accordingly through our proposed approach using real data. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Not Available | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | p-value | en_US |
dc.subject | Genomic data | en_US |
dc.title | Effect of influential observation in genomic prediction using LASSO diagnostic | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Indian Journal of Agricultural Sciences | en_US |
dc.publication.volumeno | 90 | en_US |
dc.publication.pagenumber | 1155-1159 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | https://doi.org/10.1038/s41598-020-65323-3 | en_US |
dc.publication.authorAffiliation | ICAR::Indian Agricultural Statistics Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.naasrating | 8.74 | - |
Appears in Collections: | AEdu-IASRI-Publication |
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