Classification in segmented regression problems
Copyright policy ) Cathy W. S. Chen; Jennifer So-Kuen Chan; Mike K. P. So; Kevin K. M. Lee;
Classification in segmented regression problems
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China (People's Republic of)
- Feng Chia University Taiwan
- Hong Kong Polytechnic University China (People's Republic of)
- University of Sydney Australia
- Hong Kong University of Science and Technology (香港科技大學) China (People's Republic of)
Mixture model, mixture model, Data augmentation, Classification and discrimination; cluster analysis (statistical aspects), MCMC, Bayesian inference, 310, deviance information criterion, Segmented regression, Change point, change point, Deviance information criterion, segmented regression, data augmentation
Mixture model, mixture model, Data augmentation, Classification and discrimination; cluster analysis (statistical aspects), MCMC, Bayesian inference, 310, deviance information criterion, Segmented regression, Change point, change point, Deviance information criterion, segmented regression, data augmentation
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 3
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