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A comparison of evidential networks and compositional models

Jiřina Vejnarová (2014)

Kybernetika

Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will...

A note on the IPF algorithm when the marginal problem is unsolvable

Claudio Asci, Mauro Piccioni (2003)

Kybernetika

In this paper we analyze the asymptotic behavior of the IPF algorithm for the problem of finding a 2x2x2 contingency table whose pair marginals are all equal to a specified 2x2 table, depending on a parameter. When this parameter lies below a certain threshold the marginal problem has no solution. We show that in this case the IPF has a “period three limit cycle” attracting all positive initial tables, and a bifurcation occur when the parameter crosses the threshold.

A review of canonical coordinates and an alternative to correspondence analysis using Hellinger distance.

C. Radhakrishna Rao (1995)

Qüestiió

In this paper a general theory of canonical coordinates is developed for reduction of dimensionality in multivariate data, assessing the loss of information and plotting higher dimensional data in two or three dimensions for visual displays. The theory is applied to data in two way tables with variables in one category and samples (individual or populations) in the other. Two types of data are considered, one with continuous measurements on the variables and another with frequencies of attributes....

An exact procedure for 2 x 2 x 2 contingency tables.

Wolf-Rüdiger Heilmann (1978)

Stochastica

If n independent observations, categorized according to three schemes with two categories in each scheme, have been taken, it is customary to summarize the data in a 2 x 2 x 2 contingency table (...)

An exploratory canonical analysis approach for multinomial populations based on the φ -divergence measure

Julio A. Pardo, Leandro Pardo, María Del Carmen Pardo, K. Zografos (2004)

Kybernetika

In this paper we consider an exploratory canonical analysis approach for multinomial population based on the φ -divergence measure. We define the restricted minimum φ -divergence estimator, which is seen to be a generalization of the restricted maximum likelihood estimator. This estimator is then used in φ -divergence goodness-of-fit statistics which is the basis of two new families of statistics for solving the problem of selecting the number of significant correlations as well as the appropriateness...

Anàlisi de matrius quadrades no simètriques: un enfocament integral usant anàlisi de correspondències.

Josep Daunis i Estadella, Tomàs Aluja Banet, Santiago Thió Fernández de Henestrosa (2002)

Qüestiió

In this paper a new integrated approach to the analysis of square non-symmetric tables is introduced by means of cortrespondence analysis. The application of correspondence analysis to such tables is not successful due to the strong role played by the diagonal values: overloaded diagonals and structural zeros. Two main families of methods of resolution are integrated in this paper. The resulting method is applied to the study of commuting between the 41 Catalan counties.

Asymptotic behaviour of a BIPF algorithm with an improper target

Claudio Asci, Mauro Piccioni (2009)

Kybernetika

The BIPF algorithm is a Markovian algorithm with the purpose of simulating certain probability distributions supported by contingency tables belonging to hierarchical log-linear models. The updating steps of the algorithm depend only on the required expected marginal tables over the maximal terms of the hierarchical model. Usually these tables are marginals of a positive joint table, in which case it is well known that the algorithm is a blocking Gibbs Sampler. But the algorithm makes sense even...

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