Multivariable ARMA systems and practicable calculations.

Edward J. Hannan

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Modelling stock returns with AR-GARCH processes.

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Financial returns are often modelled as autoregressive time series with random disturbances having conditional heteroscedastic variances, especially with GARCH type processes. GARCH processes have been intensely studied in financial and econometric literature as risk models of many financial time series. Analyzing two data sets of stock prices we try to fit AR(1) processes with GARCH or EGARCH errors to the log returns. Moreover, hyperbolic or generalized error distributions occur to...

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Principal Components Analysis deals mainly with the analysis of large data sets with multivariate structure in an observational context for exploraty purposes. The factorial planes produced will show the main oppositions between variables and individuals. However, we may be interested in going further by controlling the effect of some latent or third variable which expresses some well-defined phenomenon. We go through this by means of a graph among individuals, following the same idea...

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Weighting quantitative and qualitative variables in clustering methods.

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Description of individuals in ill-structured domains produces messy data matrices. In this context, automated classification requires the management of those kind of matrices. One of the features involved in clustering is the evaluation of distances between individuals. Then, a special function to calculate distances between individuals partially simultaneously described by qualitative and quantitative variables is required. In this paper properties and details of the metrics...

Knowledge discovery in data using formal concept analysis and random projections

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In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.