Estimation in additive models and ANOVA-like applications

Structural Constrained ANOVA-type Estimation of Gravity Panel Data Models

In most gravity model applications, general equilibrium effects are disregarded altogether or ”controlled for” by country or country-time fixed effects, and the parameter estimates on observable trade cost variables are falsely interpreted as reduced-form marginal effects rather than only direct effects of such variables on trade. This paper proposes an empirical approach which employs panel da...

Target setting in additive models with preferences and interval data

Graph Estimation with Joint Additive Models.

In recent years, there has been considerable interest in estimating conditional independence graphs in high dimensions. Most previous work has assumed that the variables are multivariate Gaussian, or that the conditional means of the variables are linear; in fact, these two assumptions are nearly equivalent. Unfortunately, if these assumptions are violated, the resulting conditional independenc...

PAC-Bayesian Estimation and Prediction in Sparse Additive Models

The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption (p ≫ n paradigm). A PAC-Bayesian strategy is investigated, delivering oracle inequalities in probability. The implementation is performed through recent outcomes in high-dimensional MCMC algorithms, and the performance of our method is assessed on simulated data.

Estimation and Variable Selection in Additive Nonparametric Regression Models 1

Additive regression models have been shown to be useful in many situations. Numerical estimation of these models is usually done using the back-tting technique. This iterative numerical procedure converges very fast but has the disadvantage of a complicated`hat matrix.' This paper proposes an estimator with an explicit`hat matrix' which does not use backktting. The asymptotic normality of the e...