Displaying similar documents to “Medidas de centralización multidimensionales (ley fuerte de los grandes números).”

Un teorema de convergencia con aplicación a la inferencia bayesiana.

Eusebio Gómez Sánchez-Manzano (1986)

Trabajos de Estadística

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A theorem is proved showing that, assuming some boundary conditions, the following hypotheses: 1. {Xn} is a sequence of continuous random variables which approaches in probability to a numerical sequence {an}, 2. {Yn} is another sequence of random variables such that, for all n, the density function of Yn is proportional to the product of the density of Xn...

Generalización del teorema de Hanson y Russo para B-variables aleatorias.

Víctor Hernández, Juan J. Romo (1986)

Trabajos de Estadística

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En este trabajo se presenta una generalización de un teorema de D. L. Hanson y R. P. Russo (1981) para variables aleatorias i.i.d. que toman valores en un espacio de Banach separable (B-variables), en el esquema más general de la ley de Marcinkiewicz y Zygmund. Imponiendo condiciones sobre los momentos y el tipo Rademacher del espacio se obtienen resultados de la forma máx(np/α≤j≤n) j-1/p ||S

Convergencias en G(H).

M.ª Carmen de las Obras Loscertales y Nasarre (1980)

Revista Matemática Hispanoamericana

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Given a real separable Hilbert space H, we denote with G(H) the geometry of closed lineal subspaces of H. The weak and strong convergence of sequences of subspaces defined in (8) are characterized. If {E(n) | n ∈ N} is a strong or weak convergent sequence there exists a finite dimensional sequence with the same limit. The strong convergence is interpreted in terms of nbd-finite family, so that a sequence {E(n)...

L y L*-convergencias en G(H).

M.ª Carmen de las Obras Loscertales y Nasarre (1981)

Revista Matemática Hispanoamericana

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Given a real separable Hilbert space H, we denote with G(H) the geometry of closed linear subspaces of H. The strong convergence of sequences of subspaces is shown to be a L*-convergence and the weak convergence a L-convergence. The smallest L*-convergence containing the weak convergence is found, and the orthogonal image of the strong convergence, which is also a L*-convergence, is defined.

Semi-recorrido condicionado (expresión asintótica de la r-esperanza condicionada).

Juan Antonio Cuesta Albertos, Carlos Matrán Bea (1983)

Trabajos de Estadística e Investigación Operativa

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In a probability space (Ω,σ,P), for α ⊂ σ a sub-σ field, in general the best approximation in L by elements of L(α) has not a unique solution. For the election between these, we prove the convergence P-almost surely of the conditional r-means, when r → ∞, to one solution, which we call conditional mid-range. This is characterized for each ω ∈ Ω by the mid-range, of one regular conditional distribution Q(ω, ·).

Teorema de Ramsey aplicado a álgebras de Boole.

F. Benítez Trujillo (1990)

Collectanea Mathematica

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Some properties of Boolean algebras are characterized through the topological properties of a certain space of countable sequences of ordinals. For this, it is necessary to prove the Ramsey theorems for an arbitrary infinite cardinal. Also, we define continuous mappings on these spaces from vector measures on the algebra.

Esperanza condicionada para probabilidades finitamente aditivas.

Luis A. Sarabia (1982)

Trabajos de Estadística e Investigación Operativa

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Let (Ω, θ, J) be a finitely additive probabilistic space formed by any set Ω, an algebra of subsets θ and a finitely additive probability J. In these conditions, if F belongs to V1(Ω, θ, J) there exists f, element of the completion of L1(Ω, θ, J), such that F(E) = ∫E f dJ for all E of θ and conversely. The integral representation gives sense to the following result, which is the objective of this paper, in terms...

Convergencia del vector de probabilidad a posteriori bajo una distribución predictiva.

Julián de la Horra (1986)

Trabajos de Estadística

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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...