Abstract. Of a11 the characterizations of Ule normal distribution, three landmarks are the theorems of Bernstein and Skitovitch wncern-ing independence of linear forms and the theorem of Geary concerning independence of sample mean and variance. In this note, ideas from several proofs of these theorems are distilled to give unified proofs which depend mostly on simple probability and characteristic function concepts. I. Introduction. In this note we present proofs of three characterization theorems: those of Bernstein and of Skitovitch concerning independence of linear forms and Geary's Theorem which concerns independence of sample mean and variance. Part of the motivation for this work was the realization that these three important th...
In classical probability there are known many characterization of probability measures by independen...
19 pages, 1 article*Detailed Proofs (Class Notes) of Necessary and Sufficient Conditions for Indepen...
In classical probability there are known many characterization of probability measures by independen...
International audienceIn this paper, we present three remarkable properties of the normal distributi...
The problem of determining a statistical population belonging to a certain class of distributions is...
Texte intégral sur le site: https://www.scienpress.comIn this paper, we present three remarkable pro...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Chistyakov G, Götze F. Independence of linear forms with random coefficients. PROBABILITY THEORY AND...
AbstractLet X1, X2,…, be independent, identically distributed random variables. Suppose that the lin...
For some cases it may be permissible to assume that the correlation between each two normal random v...
AbstractIf X1 and X2 are independent and identically distributed (i. i. d.) with finite variance, th...
The normal law is characterised through the local independence of certain statistics
In classical probability there are known many characterization of probability measures by independen...
19 pages, 1 article*Detailed Proofs (Class Notes) of Necessary and Sufficient Conditions for Indepen...
In classical probability there are known many characterization of probability measures by independen...
International audienceIn this paper, we present three remarkable properties of the normal distributi...
The problem of determining a statistical population belonging to a certain class of distributions is...
Texte intégral sur le site: https://www.scienpress.comIn this paper, we present three remarkable pro...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Texte intégral sur le site: https://www.scienpress.comInternational audienceIn this paper, we presen...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Elementary proof of the independence of mean and variance of samples from a normal distribution. Usu...
Chistyakov G, Götze F. Independence of linear forms with random coefficients. PROBABILITY THEORY AND...
AbstractLet X1, X2,…, be independent, identically distributed random variables. Suppose that the lin...
For some cases it may be permissible to assume that the correlation between each two normal random v...
AbstractIf X1 and X2 are independent and identically distributed (i. i. d.) with finite variance, th...
The normal law is characterised through the local independence of certain statistics
In classical probability there are known many characterization of probability measures by independen...
19 pages, 1 article*Detailed Proofs (Class Notes) of Necessary and Sufficient Conditions for Indepen...
In classical probability there are known many characterization of probability measures by independen...