Univariate generalized additive models for simulated stationary and non-stationary generalized Pareto distribution
Generalized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study...
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Main Authors: | Behzadi, Mostafa, Adam, Mohd Bakri, Fitrianto, Anwar |
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Format: | Article |
Language: | English |
Published: |
Science Publications
2017
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Online Access: | http://psasir.upm.edu.my/id/eprint/63632/1/Univariate%20Generalized%20Additive%20Models%20for%20Simulated%20Stationary%20and%20Non-Stationary%20Generalized%20Pareto%20Distribution.pdf http://psasir.upm.edu.my/id/eprint/63632/ |
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