Abstract
This paper presents an analysis of the space, known in the theory of reliability, of observational gross errors or blunders absolutely undetectable in the least-squares estimation process in linear Gauss-Markov models. The analysis is based on a general relationship linking the observational disturbances and a model response. Although the definition of this space is identical with that given by [l] it is arrived at in a slightly different way. Several properties of this space are formulated, one of them showing its connection with the reliability level of a model with uncorrelated observations. Although the linearized models are included in the theory, the approach applied to them, being basically a simple extension of that proposed for linear models, can not be considered as a complete proposal for practical purposes. The theory is illustrated with examples taken from engineering surveys.
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