A propos du choix aléatoire des réponses justes et de la réussite de l'examen programmé
À propos du théorème de Gauss-Markov
À propos d'un résultat de Brailovsky concernant une probabilité d'erreur en analyse discriminante
A proposal of an indicator as an auxiliary variable in cokriging analysis.
A proximity based macro stress testing framework
In this a paper a non-linear macro stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It is embedded in a framework, in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset, allowing to estimate a stressed future state. It will be shown that contagion can be directly derived from the proximities while...
A quantile goodness-of-fit test applicable to distributions with non-differentiable densities
A quantile goodness-of-fit test for Cauchy distribution, based on extreme order statistics
A test statistic for testing goodness-of-fit of the Cauchy distribution is presented. It is a quadratic form of the first and of the last order statistic and its matrix is the inverse of the asymptotic covariance matrix of the quantile difference statistic. The distribution of the presented test statistic does not depend on the parameter of the sampled Cauchy distribution. The paper contains critical constants for this test statistic, obtained from simulations for each sample size considered....
Time Series with Approximated Beta Marginal
A rank decision rule for a combined problem of testing and classification
A recursion formula for expected negative and positive powers of the central Wishart distribution.
We use Haff's fundamental identity to express the expectation of Sp in lower-order terms, where S follows the central Wishart distribution.
A recursive nonparametric estimator for the transition kernel of a piecewise-deterministic Markov process
In this paper, we investigate a nonparametric approach to provide a recursive estimator of the transition density of a piecewise-deterministic Markov process, from only one observation of the path within a long time. In this framework, we do not observe a Markov chain with transition kernel of interest. Fortunately, one may write the transition density of interest as the ratio of the invariant distributions of two embedded chains of the process. Our method consists in estimating these invariant...
A recursive robust Bayesian estimation in partially observed financial market
I propose a nonlinear Bayesian methodology to estimate the latent states which are partially observed in financial market. The distinguishable character of my methodology is that the recursive Bayesian estimation can be represented by some deterministic partial differential equation (PDE) (or evolution equation in the general case) parameterized by the underlying observation path. Unlike the traditional stochastic filtering equation, this dynamical representation is continuously dependent on the...
A regression characterization of inverse Gaussian distributions and application to EDF goodness-of-fit tests.
A Relationship between Efficiencies of Marginal Designs and the Product Design.
A remark on associative copulas
A method for producing associative copulas from a binary operation and a convex function on an interval is described.
A remark on existence of statistical functionals
A Remark on Lehmann-Unbiased Estimators for Scale Resp. Location Parameters.
A remark on models of Box-Jenkins type
A Remark on Robustness of Linear Best Estimates.
A repeated imitation model with dependence between stages: Decision strategies and rewards
Adversarial decision making is aimed at determining strategies to anticipate the behavior of an opponent trying to learn from our actions. One defense is to make decisions intended to confuse the opponent, although our rewards can be diminished. This idea has already been captured in an adversarial model introduced in a previous work, in which two agents separately issue responses to an unknown sequence of external inputs. Each agent's reward depends on the current input and the responses of both...