Maximum Likelihood Estimation of Parameters in Generalized Functional Linear Model

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
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.

Keywords:

Covariance operator , Eigenfunctions , Functional regression , Generalized functional linear model , Karhunen–Loève expansion

Language:
Persian
Published:
Andishe-ye Amari, Volume:24 Issue: 2, 2020
Pages:
43 to 54
https://www.magiran.com/p2140112