Logistic regression for circular data

Al-Daffaie, Kadhem and Khan, Shahjahan (2017) Logistic regression for circular data. In: 3rd ISM International Statistical Conference 2016 (ISM III): Bringing Professionalism and Prestige in Statistics, 9-11 Aug 2016, Kuala Lumpur, Malaysia.

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This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of
Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Accepted version deposited in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 31 Jan 2017 08:15
Last Modified: 19 Sep 2018 01:21
Uncontrolled Keywords: logistic regression, circular data, maximum likelihood method
Fields of Research : 01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
01 Mathematical Sciences > 0104 Statistics > 010405 Statistical Theory
05 Environmental Sciences > 0502 Environmental Science and Management > 050299 Environmental Science and Management not elsewhere classified
Identification Number or DOI: 10.1063/1.4982860
URI: http://eprints.usq.edu.au/id/eprint/30467

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