Estimating the conditional tail expectation in the case of heavy-tailed losses.
Estimation automatique de la densité
Estimation by Minimum-Discrepancy Methods
Estimation de la densité par projection sur un sous-espace de dimension finie
Estimation des densités : risque minimax
Estimation fonctionnelle. Risque minimax
Estimation in autoregressive model with measurement error
Consider an autoregressive model with measurement error: we observe Zi = Xi + εi, where the unobserved Xi is a stationary solution of the autoregressive equation Xi = gθ0(Xi − 1) + ξi. The regression function gθ0 is known up to a finite dimensional parameter θ0 to be estimated. The distributions of ξ1 and X0 are unknown and gθ belongs to a large class of parametric regression functions. The distribution of ε0is completely known. We propose an estimation procedure with a new criterion computed as...
Estimation non paramétrique de la densité par histogrammes généralisés
Estimation non paramétrique de la fonction de hasard pour des observations dépendantes
Estimation non paramétrique de la régression par la méthode du noyau : propriété de convergence asymptotiquememt normale indépendante
Estimation non paramétrique de l'espérance et de la variance de la loi de reproduction d'un processus de ramification
Estimation non paramétrique du -quantile conditionnel et ses dérivées partielles
Estimation non-paramétrique par noyaux : régression polynomiale mobile
Estimation of a smoothness parameter by spline wavelets
We consider the smoothness parameter of a function f ∈ L²(ℝ) in terms of Besov spaces , . The existing results on estimation of smoothness [K. Dziedziul, M. Kucharska and B. Wolnik, J. Nonparametric Statist. 23 (2011)] employ the Haar basis and are limited to the case 0 < s*(f) < 1/2. Using p-regular (p ≥ 1) spline wavelets with exponential decay we extend them to density functions with 0 < s*(f) < p+1/2. Applying the Franklin-Strömberg wavelet p = 1, we prove that the presented estimator...
Estimation of a System Reliability by Nonparametric Techniques
Estimation of contamination level in model of contaminacy with general neighbourhoods
Estimation of reduced Palm distributions by random methods for Cox processes with unknown probability law
Let , i ≥ 1, be i.i.d. observable Cox processes on [a,b] directed by random measures Mi. Assume that the probability law of the Mi is completely unknown. Random techniques are developed (we use data from the processes ,..., to construct a partition of [a,b] whose extremities are random) to estimate L(μ,g) = E(exp(-(N(g) - μ(g))) | N - μ ≥ 0).
Estimation of summary characteristics from replicated spatial point processes
Summary characteristics play an important role in the analysis of spatial point processes. We discuss various approaches to estimating summary characteristics from replicated observations of a stationary point process. The estimators are compared with respect to their integrated squared error. Simulations for three basic types of point processes help to indicate the best way of pooling the subwindow estimators. The most appropriate way depends on the particular summary characteristic, edge-correction...
Estimation of the drift function for Ito processes and a class of semimartingales via histogram sieve
A histogram sieve estimator of the drift function in Ito processes and some semimartingales is constructed. It is proved that the estimator is pointwise and L¹ consistent and its finite-dimensional distributions are asymptotically normal. Our approach extends the results of Leśkow and Różański (1989a).
Estimation of the hazard function in a semiparametric model with covariate measurement error
We consider a failure hazard function, conditional on a time-independent covariate Z, given by . The baseline hazard function and the relative risk both belong to parametric families with . The covariate Z has an unknown density and is measured with an error through an additive error model U = Z + ε where ε is a random variable, independent from Z, with known density . We observe a n-sample (Xi, Di, Ui), i = 1, ..., n, where Xi is the minimum between the failure time and the censoring time, and...