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Journal ArticleDOI

An Introduction to Linear Statistical Models, Volume I.

William G. Madow, +1 more
- 01 Oct 1961 - 
- Vol. 68, Iss: 8, pp 819
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This article is published in American Mathematical Monthly.The article was published on 1961-10-01. It has received 74 citations till now. The article focuses on the topics: Volume (compression) & Statistical model.

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Some Methodological Issues in Cohort Analysis of Archival Data

TL;DR: Walton et al. as discussed by the authors discuss discipline, method and community power: a note on the sociology of knowledge, and the vertical axis of community organization and the structure of power.
Journal ArticleDOI

Estimating covariance functions for longitudinal data using a random regression model

TL;DR: A method is described to estimate genetic and environmental covariance functions for traits measured repeatedly per individual along some continuous scale directly from the data by restricted maximum likelihood by relying on the equivalence of a covariance function and a random regression model.
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Probabilities of Non-Positive Definite between-Group or Genetic Covariance Matrices

William G. Hill, +1 more
- 01 Sep 1978 - 
TL;DR: In this article, the probability that the estimated between-group covariance matrix is not positive deJinite is computed for the balanced single classlfication multivariate analysis of variance with random effects.
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Estimates of direct and maternal covariance functions for growth of Australian beef calves from birth to weaning

TL;DR: Analysis of records for birth and subsequent, monthly weights until weaning on beef calves of two breeds in a selection experiment identified similar patterns of variation for both breeds, with maternal effects considerably more important in purebred Polled Herefords than a four-breed synthetic.
Journal ArticleDOI

A Simple Method for the Construction of Empirical Confidence Limits for Economic Forecasts

TL;DR: In this paper, a simple method for the construction of empirical confidence intervals for time series forecasts is described, which is particularly useful when the mechanism generating the series cannot be fully identified from the available data or when limits based on more standard considerations are difficult to obtain.