# My PhD Project

# My PhD Project

## Publications

### Regression modelling using priors depending on Fisher information covariance kernels (I-priors)

Regression analysis is undoubtedly an important tool to understand the relationship between one or more explanatory and independent …

### iprior: An R Package for Regression Modelling using I-priors

This is an overview of the R package iprior, which implements a unified methodology for fitting parametric and nonparametric regression …

## Talks

### Binary and Multinomial Regression using Fisher Information Covariance Kernels (I-priors)

In a regression setting, we define an I-prior as a Gaussian process prior on the regression function with covariance kernel equal to …

### Regression Modelling with I-Priors

This is an overview of a unified methodology for fitting parametric and nonparametric regression models, including additive models, …

### Binary probit regression with I-priors

An extension of the I-prior methodology to binary response data is explored. Starting from a latent variable approach, it is assumed …

### I-priors in Bayesian Variable Selection: From Reproducing Kernel Hilbert Spaces to Hamiltonian Monte Carlo

I-priors are a class of objective priors for regression functions which makes use of its Fisher information in a function space …

### Two-stage Bayesian variable selection for linear models using I-priors

In a previous work, I showed that the use of I-priors in various linear models can be considered as a solution to the over-fitting …

### Regression Modelling using I-Priors

The I-prior methodology is a new modelling technique which aims to improve on maximum likelihood estimation of linear models when the …