A Less Sensitive Linear Detector for the Change Point Based on Kernel Smoothing Method.
Adaptive procedures
Adaptive wavelet estimation of the diffusion coefficient under additive error measurements
We study nonparametric estimation of the diffusion coefficient from discrete data, when the observations are blurred by additional noise. Such issues have been developed over the last 10 years in several application fields and in particular in high frequency financial data modelling, however mainly from a parametric and semiparametric point of view. This paper addresses the nonparametric estimation of the path of the (possibly stochastic) diffusion coefficient in a relatively general setting. By...
Announcement
Application des lois non paramétriques dans les systèmes d’attente et la théorie de renouvellement
Les distributions non paramétriques de survie trouvent, de plus en plus, des applications dans des domaines très variés, à savoir : théorie de fiabilité et analyse de survie, files d’attente, maintenance, gestion de stock, théorie de l’économie, L’objet de ce travail est d’utiliser les bornes inférieures et supérieures (en terme de la moyenne) des fonctions de fiabilité appartenant aux classes de distribution de type et , présentées par Sengupta (1994), pour l’évaluation de certaines caractéristiques....
Application des lois non paramétriques dans les systèmes d'attente et la théorie de renouvellement
Les distributions non paramétriques de survie trouvent, de plus en plus, des applications dans des domaines très variés, à savoir: théorie de fiabilité et analyse de survie, files d'attente, maintenance, gestion de stock, théorie de l'économie, ... L'objet de ce travail est d'utiliser les bornes inférieures et supérieures (en terme de la moyenne) des fonctions de fiabilité appartenant aux classes de distribution de type IFR, DFR, NBU et NWU, présentées par Sengupta (1994), pour l'évaluation de...
Asymptotic covariances of empirical processes
Asymptotic distribution of rank statistics used for multivariate testing symmetry (Preliminary communication)
Asymptotic normality and convergence rates of linear rank statistics under alternatives
Bayesian approach for joint longitudinal and time-to-event data with survival fraction.
Bayesian density estimation.
Bias-robust estimates based on order statistics and spacings in the exponential model
Blended -divergences with examples
Several new examples of divergences emerged in the recent literature called blended divergences. Mostly these examples are constructed by the modification or parametrization of the old well-known phi-divergences. Newly introduced parameter is often called blending parameter. In this paper we present compact theory of blended divergences which provides us with a generally applicable method for finding new classes of divergences containing any two divergences and given in advance. Several examples...
Convergence pour les processus empiriques éclatés
Efecto de un proceso de poda en algunos coeficientes de asociación derivados del estadístico χ2.
Estimación paramétrica bayesiana no paramétrica de funciones de supervivencia con observaciones parcialmente censuradas.
The problem of nonparametric estimation of a survival function based on a partially censored on the right sample is established in a Bayesian context, using parametric Bayesian techniques. Estimates are obtained considering neutral to the right processes, they are particularized to some of them, and their asymptotic properties are studied from a Bayesian point of view. Finally, an application to a Dirichlet process is simulated.
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...
Evaluating improvements of records
We evaluate the extreme differences between the consecutive expected record values appearing in an arbitrary i.i.d. sample in the standard deviation units. We also discuss the relevant estimates for parent distributions coming from restricted families and other scale units.
Explicit Karhunen-Loève expansions related to the Green function of the Laplacian
Karhunen-Loève expansions of Gaussian processes have numerous applications in Probability and Statistics. Unfortunately the set of Gaussian processes with explicitly known spectrum and eigenfunctions is narrow. An interpretation of three historical examples enables us to understand the key role of the Laplacian. This allows us to extend the set of Gaussian processes for which a very explicit Karhunen-Loève expansion can be derived.
Exponential bounds for multivariate self-normalized sums.