-contiguity in nonparametric testing problems
-optimal rejection with preview: geometric constraints and dynamic feedforward solutions via spectral factorization
In this work, a feedforward dynamic controller is devised in order to achieve H2-optimal rejection of signals known with finite preview, in discrete-time systems. The feedforward approach requires plant stability and, more generally, robustness with respect to parameter uncertainties. On standard assumptions, those properties can be guaranteed by output dynamic feedback, while dynamic feedforward is specifically aimed at taking advantage of the available preview of the signals to be rejected, in...
Handcuffed Designs.
Handwritten digit recognition by combined classifiers
Classifiers can be combined to reduce classification errors. We did experiments on a data set consisting of different sets of features of handwritten digits. Different types of classifiers were trained on these feature sets. The performances of these classifiers and combination rules were tested. The best results were acquired with the mean, median and product combination rules. The product was best for combining linear classifiers, the median for -NN classifiers. Training a classifier on all features...
Harmonic analysis in value at risk calculations.
Value at Risk is a measure of risk exposure of a portfolio and is defined as the maximum possible loss in a certain time frame, typically 1-20 days, and within a certain confidence, typically 95%. Full valuation of a portfolio under a large number of scenarios is a lengthy process. To speed it up, one can make use of the total delta vector and the total gamma matrix of a portfolio and compute a Gaussian integral over a region bounded by a quadric. We use methods from harmonic analysis to find approximate...
Hazard rate model and statistical analysis of a compound point process
A stochastic process cumulating random increments at random moments is studied. We model it as a two-dimensional random point process and study advantages of such an approach. First, a rather general model allowing for the dependence of both components mutually as well as on covariates is formulated, then the case where the increments depend on time is analyzed with the aid of the multiplicative hazard regression model. Special attention is devoted to the problem of prediction of process behaviour....
Heavy tailed durations of regional rainfall
Durations of rain events and drought events over a given region provide important information about the water resources of the region. Of particular interest is the shape of upper tails of the probability distributions of such durations. Recent research suggests that the underlying probability distributions of such durations have heavy tails of hyperbolic type, across a wide range of spatial scales from 2 km to 120 km. These findings are based on radar measurements of spatially averaged rain rate...
Hellinger integrals, contiguity and entire separation
Hermite Series Estimators for Probability Densities.
Heterogeneity and model uncertainty in Bayesian regression models.
Hidden Markov model likelihoods and their derivatives behave like i.i.d. ones
Hierarchical Analysis: Classification with Ordinal Object Dissimilarities.
Hierarchical text categorization using fuzzy relational thesaurus
Text categorization is the classification to assign a text document to an appropriate category in a predefined set of categories. We present a new approach for the text categorization by means of Fuzzy Relational Thesaurus (FRT). FRT is a multilevel category system that stores and maintains adaptive local dictionary for each category. The goal of our approach is twofold; to develop a reliable text categorization method on a certain subject domain, and to expand the initial FRT by automatically added...
High level quantile approximations of sums of risks
The approximation of a high level quantile or of the expectation over a high quantile (Value at Risk (VaR) or Tail Value at Risk (TVaR) in risk management) is crucial for the insurance industry.We propose a new method to estimate high level quantiles of sums of risks. It is based on the estimation of the ratio between the VaR (or TVaR) of the sum and the VaR (or TVaR) of the maximum of the risks. We show that using the distribution of the maximum to approximate the VaR is much better than using...
High-dimensional gaussian model selection on a gaussian design
We consider the problem of estimating the conditional mean of a real gaussian variable Y=∑i=1pθiXi+ɛ where the vector of the covariates (Xi)1≤i≤p follows a joint gaussian distribution. This issue often occurs when one aims at estimating the graph or the distribution of a gaussian graphical model. We introduce a general model selection procedure which is based on the minimization of a penalized least squares type criterion. It handles a variety of problems such as ordered and complete variable selection,...
Hilbert-space methods in experimental design
Histogram selection in non Gaussian regression
We deal with the problem of choosing a piecewise constant estimator of a regression function s mapping into . We consider a non Gaussian regression framework with deterministic design points, and we adopt the non asymptotic approach of model selection via penalization developed by Birgé and Massart. Given a collection of partitions of , with possibly exponential complexity, and the corresponding collection of piecewise constant estimators, we propose a penalized least squares criterion which...
Histoire et préhistoire de l'analyse des données
Histoire et préhistoire de l'analyse des données
Histoire et préhistoire de l'analyse des données