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Obtaining information from time data statistical analysis in human component system studies. (I). Methods and performances

Authors
Journal
Information Sciences
0020-0255
Publisher
Elsevier
Publication Date
Volume
132
Identifiers
DOI: 10.1016/s0020-0255(01)00063-9
Keywords
  • Data Characterizing
  • Data Mining
  • Exploratory Statistics
  • Confirmatory Statistics
  • Statistical Method Assessment
Disciplines
  • Design

Abstract

Abstract This article states the problem of the time data exploration as the succession of the many analysis paths taken prior to obtaining results, results which are initially in a latent state. The initial data – obtained by an experiment or an observation design – are placed within a hyperparallelepiped HP0 where the directions correspond to factors established a priori and each cell contains a multidimensional signal. An analysis path is thus considered to be a progressive information transformation of the time data including up to five stages – data characterizing, scale transformation, data shaping, statistical analysis method application and result presentation. For each stage, a non-exhaustive set of methods is proposed. To assess the performance of each stage, several methods are suggested. More particularly, the evaluation of the first stage is considered either in terms of a cardinality reduction between the input and output hyperparallelepipeds HP0 and HP1 or in terms of distance comparisons between the cells of HP0 and HP1. A discussion of the main statistical behaviors encountered in the literature is included.

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