Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model
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Abstract:
Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to estimate the model parameters. Finally, in a simulation study and two practical examples, the model and methods presented are implemented.
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Journal title
volume 24 issue 2
pages 43- 54
publication date 2020-03
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