QFASA R Package

Simple item page
dc.contributor.advisorStewart, Connie
dc.contributor.authorKamerman, Justin
dc.date.accessioned2023-03-01T16:46:32Z
dc.date.available2023-03-01T16:46:32Z
dc.date.issued2019
dc.date.updated2023-03-01T15:03:16Z
dc.description.abstractThe primary contribution of this project is to package R source code created to support the fitting and evaluation of Quantitative Fatty Acid Signature Analysis (QFASA) models into a FOSS module available on CRAN. The existing code is widely used by the QFASA community but is inconsistently documented and maintained. This makes it difficult for new users to get up to speed with new and current QFASA methodologies, and to distribute code fixes and improvements. Creating an R package is a well-defined process and encourages the use of software engineering best practices and the production of well-documented modules that are easy to install and maintain. This report describes the process of diet estimation via the QFASA methodology and reviews some of the underlying statistical methodologies. We detail the R packaging process and our interaction with CRAN to publish the package, and our implementation of parallel computing methods to improve the speed and efficiency of model inference by making use of multi-core processors. Finally, for comparison, we review a similar QFASA module, qfasar, which was released subsequently.
dc.description.copyright© Justin Kamerman, 2019
dc.formattext/xml
dc.format.extentix, 83 pages
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/14464
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.titleQFASA R Package
dc.typemaster thesis
thesis.degree.disciplineMathematics and Statistics
thesis.degree.fullnameMaster of Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
item.pdf
Size:
1.36 MB
Format:
Adobe Portable Document Format
Download

Collections