A view on filtering of continuous data signals
Adaptive tests for periodic signal detection with applications to laser vibrometry
Initially motivated by a practical issue in target detection via laser vibrometry, we are interested in the problem of periodic signal detection in a Gaussian fixed design regression framework. Assuming that the signal belongs to some periodic Sobolev ball and that the variance of the noise is known, we first consider the problem from a minimax point of view: we evaluate the so-called minimax separation rate which corresponds to the minimal l2-distance between the signal and zero so that the detection...
Adaptive tests of homogeneity for a Poisson process
We propose to test the homogeneity of a Poisson process observed on a finite interval. In this framework, we first provide lower bounds for the uniform separation rates in -norm over classical Besov bodies and weak Besov bodies. Surprisingly, the obtained lower bounds over weak Besov bodies coincide with the minimax estimation rates over such classes. Then we construct non-asymptotic and non-parametric testing procedures that are adaptive in the sense that they achieve, up to a possible logarithmic...
Admissibility of Generalized Bayes Estimators in An One Parameter Nonregular Family.
Admissibility of Henderson's estimators for three variance components
Admissible and Minimax Estimators of ...r in the Gamma Distribution with Truncated Parameter Space.
Admissible estimators in the general multivariate linear model with respect to inequality restricted parameter set.
Admissible invariant estimators in a linear model
Let be observation vector in the usual linear model with expectation and covariance matrix known up to a multiplicative scalar, possibly singular. A linear statistic is called invariant estimator for a parametric function if its MSE depends on only through . It is shown that is admissible invariant for , if and only if, it is a BLUE of in the case when is estimable with zero variance, and it is of the form , where and is an arbitrary BLUE, otherwise. This result is used in...
Advanced approach for the public transportation regulation system based on cybercars
In the last decade, the authorities require the use of safe, comfortable vehicles to assure a door to door aspect with respect of environment in the urban context. In this paper, we propose an advanced approach of transport regulation where we integrate cybercars into a regulation process as an alternative in disruption cases. For that, we propose an ITS architecture including public transportation and cybercars into the same framework. We will show that collaboration between these two systems...
Algorithm. 45. Bayes factor test. An algorithm giving tables for a non-parametric two-sample test of the Bayesian discrimination power of an observed factor
Algorithmical complexity of some statistical decision processes. I
Algorithmical complexity of some statistical decision processes. II
Algunos progresos y problemas en la Ciencia de la decisión.
The study of decision making and problem solving has attracted much attention. Since the middle of this century the notion of rational decision making was associated with expected utility maximization, albeit in a very different way than D. Bernoulli (1738) envisioned. For decisions under risk, Von Neumann and Morgenstern (1947) formulated the axioms for expected utility. For decisions under uncertainty Savage (1954) developed the axioms leading simultaneously to subjective probability and expected...
An admissible estimator of a lower-bounded scale parameter under squared-log error loss function
Estimation in truncated parameter space is one of the most important features in statistical inference, because the frequently used criterion of unbiasedness is useless, since no unbiased estimator exists in general. So, other optimally criteria such as admissibility and minimaxity have to be looked for among others. In this paper we consider a subclass of the exponential families of distributions. Bayes estimator of a lower-bounded scale parameter, under the squared-log error loss function with...
An algorithm for Bayes parameter identification with quadratic asymmetrical loss function
An alternative method for construction of optimal sequential questionnaires
An Application of Discriminant Analysis and Artificial Neural Networks to Classification Problems
An Approach for Selecting Appropriate Methods for Treating Uncertainty in Knowledge Based Systems
An empirical Bayes derivation of best linear unbiased predictors.
An Identity Concerning a Wishart Matrix.