Factor Analysis mean centring

The log-linear model (LLM) is closely related to correspondence factor analysis (CFA). Both methods pursue the same objective, i.e. the analysis of the association (or correspondence) between the rows and columns of a contingency table. In CFA this can be obtained by means of double-closure of the data in LLM this is achieved by means of double-centring of the logarithmic data. 

Classification of lake sediments by means of factor analysis and hierarchical clustering has been reported by Hopke et. al. C1103- For a set of 79 sediment samples, 32 characteristic properties were determined (e.g. concentration of 15 elements, percent organic matter, criteria of the particle size distribution, water depth). Cluster analysis detected a single cluster for samples from the centre of the lake and three different clusters for samples from near the shore. 

In most uncertainty studies published so far (see e.g. Brown et al. (1999), Turanyi et al. (2002), Zsely et al. (2005), Zador et al. (2005a, b, 2006a) and Zsely et al. (2008)), where the uncertainties of the rate coefficients were utilised, the uncertainty of k was considered to be equal to the xmcertainty of the pre-exponential factor A. This implies that the uncertainty of parameters E and n is zero, which is an unrealistic assumption. In a global sensitivity analysis study of a turbulent reacting atmospheric plume, Ziehn et al. (2009a) demonstrated the importance of uncertainties in EIR for the reaction N0 + 03 = N02 + 02. In this case for the prediction of mean plume centre line O3 concentratiOTis, the sensitivity to the assumed value for EIR was almost a factor of 20 higher than that of the A-factor, based on input parameter uncertainty factors provided by the evaluation of Androulakis (2004, 2004). However, in this case the parameters of the Anhenius expression for the chemical reactions considered were allowed to vary independently. In fact, the characterisation of the joint uncertainty of the Arrhenius parameters is important for the reahstic calculatiOTi of the uncertainty of chemical kinetic simulation results as will be discussed in the next section. 

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