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Journal ArticleDOI

TENSOR NOTATION AND THE SAMPLING CUMULANTS OF k-STATISTICS*

E. L. Kaplan
- 01 Dec 1952 - 
- Vol. 39, pp 319-323
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This article is published in Biometrika.The article was published on 1952-12-01. It has received 66 citations till now. The article focuses on the topics: Sampling (statistics) & Ricci calculus.

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Tensor Methods in Statistics

TL;DR: In this article, the authors provide a systematic development of tensor methods in statistics, beginning with the study of multivariate moments and cumulants, and an examination of the effect of making a polynomial transformation of the original variables.
Journal ArticleDOI

The fitting of straight lines when both variables are subject to error

TL;DR: In this paper, the authors survey and comment on the solutions to the problem of obtaining consistent estimates of α and β from a sample of (x, y)s, when one makes various assumptions about properties of the errors and the true values other than those mentioned above, and when one has various kinds of "additional information" which aids in constructing these consistent estimates.
Journal ArticleDOI

Some contributions to efficient statistics in structural models: Specification and estimation of moment structures.

TL;DR: In this article, it is shown that higher order product moments yield important structural information when the distribution of variables is arbitrary, and some asymptotically distribution-free efficient estimators for such arbitrary structural models are developed.
Journal ArticleDOI

Simultaneous equation systems as moment structure models: With an introduction to latent variable models

TL;DR: In this article, the traditional econometric simultaneous equation system is reconceptualized as a random vector structural equation model and extended to deal with latent variables and a wider variety of structural phenomena via the Joreskog-Keesling-Wiley LISREL approach.
Journal ArticleDOI

Factor analysis for non-normal variables

TL;DR: In this paper, the main difference between our approach and more traditional approaches is that not only second order cross-products (like covariances) are utilized, but also higher order crossproducts.
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