Titlebook: Advances in Compositional Data Analysis; Festschrift in Honou Peter Filzmoser,Karel Hron,Javier Palarea-Albalade Book 2021 Springer Nature

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Aiding and Controlling Business,ices is endowed with a group operation, the componentwise product or Hadamard product. Also an inner product, identified with the ordinary inner product of the componentwise logarithm of the matrices, completes the sample space to be a Euclidean space. This situation allows to introduce two orthogon

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Aiding and Controlling Business,nly a limited number of families arising through the generalization of the Dirichlet family or the logratio normal family. This chapter tries to summarize those models and some generalizations with a special emphasis on the algebraic-geometric structure of the simplex and on the measure which is con

apropos

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Aiding and Controlling Business,ethods for the analysis of data with local variations but only a few of them are accommodated for the purposes of modelling relative structures. In this chapter, the geographically weighted regression model is introduced to analyse the relationship between the dependent variable and an explanatory v

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Aiding and Controlling Business,al analysis because they provide the relative importance of the parts of a whole. Any statistical model including variables created using the original parts should be formulated according to the geometry of the simplex. Methods based on log-ratio coordinates give a consistent framework for analyzing

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https://doi.org/10.1007/978-1-349-13832-6lity at different time points. Such data provide information on the magnitude of satisfaction as well as information on how aspects vary with respect to each other and how they contribute to the total satisfaction of each student. Data magnitude is predominant in determining variability patterns, th

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https://doi.org/10.1007/978-1-349-13832-6s for compositional data are typically applied on additive, centered, or isometric log-ratio representations of the data. Generally, methods for compositional data analysis can only be applied to observed positive entries in a data matrix. Therefore, one tries to impute missing values or measurement