Consistency of Minimum Contrast Estimators in Non-Standard Cases.
Consistent Estimation in the Presence of Incidental Parameters.
Constructing median-unbiased estimators in one-parameter families of distributions via stochastic ordering
If θ ∈ Θ is an unknown real parameter of a given distribution, we are interested in constructing an exactly median-unbiased estimator θ̂ of θ, i.e. an estimator θ̂ such that a median Med(θ̂ ) of the estimator equals θ, uniformly over θ ∈ Θ. We shall consider the problem in the case of a fixed sample size n (nonasymptotic approach).
Convergence des suites d'estimateurs ensemblistes du maximum de vraisemblance
Correction to the paper “On the two-sided quality control”
The correction sonsists of deriving correct explicit formulas for MLE of parameters of the normal distribution under the hypothesis .
Coupling a stochastic approximation version of EM with an MCMC procedure
The stochastic approximation version of EM (SAEM) proposed by Delyon et al. (1999) is a powerful alternative to EM when the E-step is intractable. Convergence of SAEM toward a maximum of the observed likelihood is established when the unobserved data are simulated at each iteration under the conditional distribution. We show that this very restrictive assumption can be weakened. Indeed, the results of Benveniste et al. for stochastic approximation with markovian perturbations are used to establish...
Coupling a stochastic approximation version of EM with an MCMC procedure
The stochastic approximation version of EM (SAEM) proposed by Delyon et al. (1999) is a powerful alternative to EM when the E-step is intractable. Convergence of SAEM toward a maximum of the observed likelihood is established when the unobserved data are simulated at each iteration under the conditional distribution. We show that this very restrictive assumption can be weakened. Indeed, the results of Benveniste et al. for stochastic approximation with Markovian perturbations are used to establish...
Covariance matrix elements estimation: special linear model without and with repeated measurement
Density estimation via best -approximation on classes of step functions
We establish consistent estimators of jump positions and jump altitudes of a multi-level step function that is the best -approximation of a probability density function . If itself is a step-function the number of jumps may be unknown.
Die Nichtkonsistenz der M.-L. Schätzer im Â?Switching Regression" Problem.
Die Schätzung des linearen Todesprozesses bei fehlerbehafteten Beobachtungen.
Directional Analysis of Fibre Processes Related to Boolean Models.
Discrete random processes with memory: Models and applications
The contribution focuses on Bernoulli-like random walks, where the past events significantly affect the walk's future development. The main concern of the paper is therefore the formulation of models describing the dependence of transition probabilities on the process history. Such an impact can be incorporated explicitly and transition probabilities modulated using a few parameters reflecting the current state of the walk as well as the information about the past path. The behavior of proposed...
Discretization problems on generalized entropies and -divergences
Effect of Outliers on the Estimation of Parameters.
Efficiency and robustness control via distorted maximum likelihood estimation
Efficient robust estimation of time-series regression models
The paper studies a new class of robust regression estimators based on the two-step least weighted squares (2S-LWS) estimator which employs data-adaptive weights determined from the empirical distribution or quantile functions of regression residuals obtained from an initial robust fit. Just like many existing two-step robust methods, the proposed 2S-LWS estimator preserves robust properties of the initial robust estimate. However, contrary to the existing methods, the first-order asymptotic behavior...
Eine Bemerkung zur Existenz erwartungstreuer Schätzer.
Einige Bemerkungen zur Theorie der Maximum Probability Schätzer.
Equivalent algorithms for estimation in linear model with conditions