Displaying similar documents to “Comparison of “anglo-saxon” and “french” three-mode methods”

Correspondence analysis and two-way clustering.

Antonio Ciampi, Ana González Marcos, Manuel Castejón Limas (2005)

SORT

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Correspondence analysis followed by clustering of both rows and columns of a data matrix is proposed as an approach to two-way clustering. The novelty of this contribution consists of: i) proposing a simple method for the selecting of the number of axes; ii) visualizing the data matrix as is done in micro-array analysis; iii) enhancing this representation by emphasizing those variables and those individuals which are 'well represented' in the subspace of the chosen axes. The approach...

Properties of a singular value decomposition based dynamical model of gene expression data

Krzysztof Simek (2003)

International Journal of Applied Mathematics and Computer Science

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Recently, data on multiple gene expression at sequential time points were analyzed using the Singular Value Decomposition (SVD) as a means to capture dominant trends, called characteristic modes, followed by the fitting of a linear discrete-time dynamical system in which the expression values at a given time point are linear combinations of the values at a previous time point. We attempt to address several aspects of the method. To obtain the model, we formulate a nonlinear optimization...

An alternative methodology for imputing missing data in trials with genotype-by-environment interaction: some new aspects

Sergio Arciniegas-Alarcón, Marisol García-Peña, Wojtek Janusz Krzanowski, Carlos Tadeu dos Santos Dias (2014)

Biometrical Letters

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A common problem in multi-environment trials arises when some genotypeby- environment combinations are missing. In Arciniegas-Alarcón et al. (2010) we outlined a method of data imputation to estimate the missing values, the computational algorithm for which was a mixture of regression and lower-rank approximation of a matrix based on its singular value decomposition (SVD). In the present paper we provide two extensions to this methodology, by including weights chosen by cross-validation...

Data probes, vertical trajectories and classification: a tentative study

David Pearson (2007)

International Journal of Applied Mathematics and Computer Science

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In this paper we introduce a method of classification based on data probes. Data points are considered as point masses in space and a probe is simply a particle that is launched into the space. As the probe passes by data clusters, its trajectory will be influenced by the point masses. We use this information to help us to find vertical trajectories. These are trajectories in the input space that are mapped onto the same value in the output space and correspond to the data classes. ...

Clustering of Symbolic Data based on Affinity Coefficient: Application to a Real Data Set

Áurea Sousa, Helena Bacelar-Nicolau, Fernando C. Nicolau, Osvaldo Silva (2013)

Biometrical Letters

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In this paper, we illustrate an application of Ascendant Hierarchical Cluster Analysis (AHCA) to complex data taken from the literature (interval data), based on the standardized weighted generalized affinity coefficient, by the method of Wald and Wolfowitz. The probabilistic aggregation criteria used belong to a parametric family of methods under the probabilistic approach of AHCA, named VL methodology. Finally, we compare the results achieved using our approach with those obtained...

Profile analysis of mothers susceptible to contaminant exposure in the Algarve region: Application of the HJ-BIPLOT method

A. Serafim, R. Company, B. Lopes, N. Silva, E. Castela, M.J. Bebianno, G. Castela (2012)

Biometrical Letters

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The HJ-BIPLOT method developed by Galindo (1986) was applied in order to identify and categorize mothers vulnerable to environmental contamination in the Algarve region (South Portugal). The application of the BIPLOT method made it possible to recognize the most important exposure routes for contamination, showing that workplace, diet and smoking habits seem the most significant factors contributing to maternal and foetal exposure vulnerability

The post randomisation method for protecting microdata.

José Gouweleeuw, Peter Kooiman, Leon Willenborg, Peter-Paul De Wolf (1998)

Qüestiió

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This paper describes the Post Randomisation Method (PRAM) for disclosure protection of microdata. Applying PRAM means that for each record in the data file according to a specified probability mechanism the score on a number of variables is changed. Since this probability mechanism is known, the characteristics of the latent true data can unbiasedly be estimated from the observed data moments in the perturbed file. PRAM is applied to categorical variables. It is shown that...