Conventional Statistical Problem with Irregular Minimax Behavior.
Convergence des suites d'estimateurs ensemblistes du maximum de vraisemblance
Convergence des surmartingales. Application aux vraisemblances partielles
Convergence en loi des H-variations d'un processus gaussien stationnaire sur R
Convergence in Distribution of Minimum-Distance Estimators.
Convergence in fractional models and applications.
Convergence model of interest rates of CKLS type
This paper deals with convergence model of interest rates, which explains the evolution of interest rate in connection with the adoption of Euro currency. Its dynamics is described by two stochastic differential equations – the domestic and the European short rate. Bond prices are then solutions to partial differential equations. For the special case with constant volatilities closed form solutions for bond prices are known. Substituting its constant volatilities by instantaneous volatilities we...
Convergence of a mimetic finite difference method for static diffusion equation.
Convergence of conditional expectations
Convergence of Ratios and Differences of two Order Statistics
Convergence of the tail probability for weighted sums of negatively orthant dependent random variables
In this research, strong convergence properties of the tail probability for weighted sums of negatively orthant dependent random variables are discussed. Some sharp theorems for weighted sums of arrays of rowwise negatively orthant dependent random variables are established. These results not only extend the corresponding ones of Cai [4], Wang et al. [19] and Shen [13], but also improve them, respectively.
Convergence of values in optimal stopping and convergence of optimal stopping times.
Convergence pour les processus empiriques éclatés
Convergence presque sûre et en moyenne des processus d'approximation stochastique, (1ère Partie) processus de Dvoretzky
Convergence rate of the distributions of normalized maximum likelihood estimators for irregular parametric families.
Convergence rates for empirical Bayes two-action problems: The uniform distribution.
Convergence rates of orthogonal series regression estimators
General conditions for convergence rates of nonparametric orthogonal series estimators of the regression function f(x)=E(Y | X = x) are considered. The estimators are obtained by the least squares method on the basis of a random observation sample (Yi,Xi), i=1,...,n, where have marginal distribution with density and Var( Y | X = x) is bounded on A. Convergence rates of the errors and for the estimator , constructed using an orthonormal system , k=1,2,..., in are obtained.
Convergencia del vector de probabilidad a posteriori bajo una distribución predictiva.
La convergencia casi segura de una sucesión de variables aleatorias, con respecto a PX,Q (distribución predictiva), se estudia en relación con la convergencia casi segura, con respecto a PX,θ (para todo θ ∈ Θ), donde {PX,θ}θ ∈ Θ es una familia de modelos de probabilidad sobre el espacio muestral χ.Como consecuencia, se estudia la convergencia casi segura del vector de probabilidad a posteriori con respecto a PX,Q.
Convex densities and their financial applications
Convexidad y simetría de la J-divergencia generalizada.
En este trabajo se caracteriza la simetría de la J-divergencia generalizada en términos del parámetro y de la función que la determina. Se plantea seguidamente la convexidad y la simetrización en función del parámetro, atendiendo a la forma de la función φ(t) que la determina. Finalmente, se revisa la convexidad en función de las variables atendiendo a la concavidad y convexidad de las funciones φ(t) y 1/φ''(t).