منابع مشابه
Generalized Functional Linear Models
We propose a generalized functional linear regression model for a regression situation where the response variable is a scalar and the predictor is a random function. A linear predictor is obtained by forming the scalar product of the predictor function with a smooth parameter function, and the expected value of the response is related to this linear predictor via a link function. If in additio...
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In this paper we present a technique for extending generalized linear models (GLM) to the situation where some of the predictor variables are observations from a curve or function. The technique is particularly useful when only fragments of each curve have been observed. We demonstrate, on both simulated and real world data sets, how this approach can be used to perform linear, logistic and cen...
متن کاملVariable Selection in Generalized Functional Linear Models.
Modern research data, where a large number of functional predictors is collected on few subjects are becoming increasingly common. In this paper we propose a variable selection technique, when the predictors are functional and the response is scalar. Our approach is based on adopting a generalized functional linear model framework and using a penalized likelihood method that simultaneously cont...
متن کاملMaximum Likelihood Estimation of Parameters in Generalized Functional Linear Model
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 esti...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2005
ISSN: 0090-5364
DOI: 10.1214/009053604000001156