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- Irène Gannaz
- 2006

This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component, and unobservable Gaussian distributed random errors. We present a wavelet thresholding based estimation procedure to estimate the components of the partial linear model by… (More)

- Irene Gannaz
- 2014

We want to analyse EEG recordings in order to investigate the phonemic categorization at a very early stage of auditory processing. This problem can be modelled by a supervised classification of functional data. Discrimination is explored via a logistic functional linear model, using a wavelet representation of the data. Different procedures are… (More)

- Irène Gannaz
- 2013

The paper deals with a generalized linear model with functional data using a wavelet representation of the signals. A reduction of dimension is first obtained through a principal component analysis. The discriminative function is then given by a loglikelihood maximization, with a LASSO penalization, in order to ensure the sparsity of the wavelet… (More)

- Irène Gannaz
- 2013

The paper deals with generalized functional regression. The aim is to estimate the influence of covariates on observations, drawn from an exponential distribution. The link considered has a semiparametric expression: if we are interested in a functional influence of some covariates, we authorize others to be modeled linearly. We thus consider a generalized… (More)

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