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- W2312400065 abstract "We consider the problem of outlier detection in bivariate exponential data fitted using the generalized linear model via Bayesian approach. We follow closely the work outlined by Unnikrishnan (2010) and present every step of the detection procedure in details. Due to the complexity of the resulting joint posterior distribution, we obtain the information on the posterior distribution from samples generated by Markov Chain Monte Carlo sampling, in particular, using either the Gibbs sampler or the Metropolis-Hastings algorithm. We use local breast cancer patients’ data to illustrate the implementation of the method." @default.
- W2312400065 created "2016-06-24" @default.
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- W2312400065 date "2015-10-01" @default.
- W2312400065 modified "2023-09-27" @default.
- W2312400065 title "Outlier Detection using Generalized Linear Model in Malaysian Breast Cancer Data" @default.
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- W2312400065 doi "https://doi.org/10.17576/jsm-2015-4410-06" @default.
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