Spherical Probable Error (Spe) and its Estimation
Spiked Dirichlet process priors for Gaussian process models.
Spurious regression.
Stabilité de l'analyse en composantes principales par rapport à une perturbation des données
Stabilité du pouvoir discriminant des facteurs par rapport à des perturbations des données en analyse linéaire discriminante
Stabilité d'un opérateur de classification
Stabilité d'un opérateur de classification
Stabilité et instabilité du risque minimax pour des variables indépendantes équidistribuées
Stability and conditional Γ-minimaxity in Bayesian inference
Two concepts of optimality corresponding to Bayesian robust analysis are considered: conditional Γ-minimaxity and stability. Conditions for coincidence of optimal decisions of both kinds are stated.
Stability and other limit laws for exit times of random walks from a strip or a halfplane
Stability estimating in optimal sequential hypotheses testing
We study the stability of the classical optimal sequential probability ratio test based on independent identically distributed observations when testing two simple hypotheses about their common density : versus . As a functional to be minimized, it is used a weighted sum of the average (under ) sample number and the two types error probabilities. We prove that the problem is reduced to stopping time optimization for a ratio process generated by with the density . For being the corresponding...
Stability in stochastic programming -- The case of unknown location parameter
Stability of a characterization of normal distributions based on the first two conditional moments.
Stability of characterizations of distribution functions using failure rate functions
Let denote the failure rate function of the . and let denote the failure rate function of the mean residual life distribution. In this paper we characterize the distribution functions for which and we estimate when it is only known that or is bounded.
Stability of invariant linearly sufficient statistics in the general Gauss-Markov model
Necessary and sufficient conditions are derived for the inclusions and to be fulfilled where , and , are some classes of invariant linearly sufficient statistics (Oktaba, Kornacki, Wawrzosek (1988)) corresponding to the Gauss-Markov models and , respectively.
Stability of stochastic optimization problems - nonmeasurable case
This paper deals with stability of stochastic optimization problems in a general setting. Objective function is defined on a metric space and depends on a probability measure which is unknown, but, estimated from empirical observations. We try to derive stability results without precise knowledge of problem structure and without measurability assumption. Moreover, -optimal solutions are considered. The setup is illustrated on consistency of a --estimator in linear regression model.
Stability, sensitivity and sensitivity of characterizations
Stable hypothesis for mixed models with balanced cross-nesting
Stable hypothesis are hypothesis that may refer either for the fixed part or for the random part of the model. We will consider such hypothesis for models with balanced cross-nesting. Generalized F tests will be derived. It will be shown how to use Monte-Carlo methods to evaluate p-values for those tests.
Stable-1/2 bridges and insurance
We develop a class of non-life reserving models using a stable-1/2 random bridge to simulate the accumulation of paid claims, allowing for an essentially arbitrary choice of a priori distribution for the ultimate loss. Taking an information-based approach to the reserving problem, we derive the process of the conditional distribution of the ultimate loss. The "best-estimate ultimate loss process" is given by the conditional expectation of the ultimate loss. We derive explicit expressions for the...
Stacked heterogeneous neural networks for time series forecasting.