Correspondence analysis of two transition tables

The case of two transition tables is considered, that is two squareasymmetric matrices of frequencies where the rows and columns of thematrices are the same objects observed at three different timepoints. Different ways of visualizing the tables, either separatelyor jointly, are examined. We generalize an existing idea where asquare matrix is descomposed into symmetric and skew-symmetric partsto two matrices, leading to a decomposition into four components: (1)average symmetric, (2) average skew-symmetric, (3) symmetricdifference from average, and (4) skew-symmetric difference fromaverage. The method is illustrated with an artificial example and anexample using real data from a study of changing values over threegenerations.

Estimation of the parameters of the gravitational-wage signal of a coalescing binary system

The statistical theory of signal detection and the estimation of its parameters are reviewed and applied to the case of detection of the gravitational-wave signal from a coalescing binary by a laser interferometer. The correlation integral and the covariance matrix for all possible static configurations are investigated numerically. Approximate analytic formulas are derived for the case of narrow band sensitivity configuration of the detector.

Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a givennoise profile affecting the respective time-of-arrival (TOA) or timedifference-of-arrival (TDOA) estimates. In the average type, methodsare evaluated in terms of the expected covariance matrix ofthe position error over an ensemble of random geometries, so thatcomparison is geometry independent. Exact semianalytical equationsand associated lower bounds (depending solely on the noiseprofile) are obtained for the average covariance matrix of the positionerror in terms of the so-called information matrix specific toeach geolocation method. Statistical channel models inferred fromfield trials are used to define realistic prior probabilities for therandom geometries. A final evaluation provides extensive resultsrelating the expected position error to channel model parametersand the number of base stations.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

Affinity distribution functions in multicomponent heterogeneous adsorption. Analytical inversion of isotherms to obtain affinity spectra

An analytical approach for the interpretation of multicomponent heterogeneous adsorption or complexation isotherms in terms of multidimensional affinity spectra is presented. Fourier transform, applied to analyze the corresponding integral equation, leads to an inversion formula which allows the computation of the multicomponent affinity spectrum underlying a given competitive isotherm. Although a different mathematical methodology is used, this procedure can be seen as the extension to multicomponent systems of the classical Sips’s work devoted to monocomponent systems. Furthermore, a methodology which yields analytical expressions for the main statistical properties (mean free energies of binding and covariance matrix) of multidimensional affinity spectra is reported. Thus, the level of binding correlation between the different components can be quantified. It has to be highlighted that the reported methodology does not require the knowledge of the affinity spectrum to calculate the means, variances, and covariance of the binding energies of the different components. Nonideal competitive consistent adsorption isotherm, widely used in metal/proton competitive complexation to environmental macromolecules, and Frumkin competitive isotherms are selected to illustrate the application of the reported results. Explicit analytical expressions for the affinity spectrum as well as for the matrix correlation are obtained for the NICCA case. © 2004 American Institute of Physics.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Factor decomposition of spatial income inequality: a revision

Duro and Esteban (1998) proposed an additive decomposition of Theil populationweighted index by four income multiplicative factors (in spatial contexts). This note makes some additional methodological points: first, it argues that interaction effects are taken into account in the factoral indexes although only in a fairly restrictive way. As a consequence, we suggest to rewrite the decomposition formula as a sum of strict Theil indexes plus the interactive terms; second, it might be instructive to aggregate some of the initial factors; third, this decomposition can be immediately extended to the between- and within-group components.

Regional decomposition of CO2 emissions in the world: a cluster analysis

The purpose of this paper is to study the possible differences among countries as CO2 emitters and to examine the underlying causes of these differences. The starting point of the analysis is the Kaya identity, which allows us to break down per capita emissions in four components: an index of carbon intensity, transformation efficiency, energy intensity and social wealth. Through a cluster analysis we have identified five groups of countries with different behavior according to these four factors. One significant finding is that these groups are stable for the period analyzed. This suggests that a study based on these components can characterize quite accurately the polluting behavior of individual countries, that is to say, the classification found in the analysis could be used in other studies which look to study the behavior of countries in terms of CO2 emissions in homogeneous groups. In this sense, it supposes an advance over the traditional regional or rich-poor countries classifications .

Regional income inequalities in Europe: an updated measurement and some decomposition results

In this paper well-known summary inequality indexes are used to explore interregional income inequalities in Europe. In particular, we mainly employ Theils’population-weighted index because of its appealing properties. Two decomposition analysis are applied. First, regional inequalities are decomposed by regional subgroups (countries). Second, intertemporal inequality changes are separated into income and population changes. The main results can be summarized as follows. First, data confirm a reduction in crossregional inequality during 1982-97. Second, this reduction is basically due to real convergence among countries. Third, currently the greater part of European interregional disparities is within-country by nature, which introduce an important challenge for the European policy. Fourth, inequality changes are due mainly to income variations, population changes playing a minor role.

An analysis of strategic paths through the decomposition of total factor productivity: the case of Spanish savings banks

The Spanish savings banks attracted quite a considerable amount of interest within the scientific arena, especially subsequent to the disappearance of the regulatory constraints during the second decade of the 1980s. Nonetheless, a lack of research identified with respect to mainstream paths given by strategic groups, and the analysis of the total factor productivity. Therefore, on the basis of the resource-based view of the firm and cluster analysis, we make use of changes in structure and performance ratios in order to identify the strategic groups extant in the sector. We attain a threeways division, which we link with different input-output specifications defining strategic paths. Consequently, on the basis of these three dissimilar approaches we compute and decompose a Hicks-Moorsteen total factor productivity index. Obtained results put forward an interesting interpretation under a multi-strategic approach, together with the setbacks of employing cluster analysis within a complex strategic environment. Moreover, we also propose an ex-post method of analysing the outcomes of the decomposed total factor productivity index that could be merged with non-traditional techniques of forming strategic groups, such as cognitive approaches.

A Multisectorial model of prices: the SAM approach

Social Accounting Matrices (SAM) are normally used to analyse the income generation process. They are also useful, however, for analysing the cost transmission and price formation mechanisms. For price contributions, Roland-Holst and Sancho (1995) used the SAM structure to analyse the price and cost linkages through a representation of the interdependence between activities, households and factors. This paper is a further analysis of the cost transmission mechanisms, in which I add the capital account to the endogenous components of the Roland-Holst and Sancho approach. By doing this I reflect the responses of prices to the exogenous shocks in savings and investment. I also present an additive decomposition of the global price effects into categories of interdependence that isolates the impact on price levels of shocks in the capital account. I use a 1994 Social Accounting Matrix to make an empirical application of the Catalan economy. Keywords: social accounting matrix, cost linkages, price transmission, capital account. JEL Classification: C63, C69, D59.

Analytic approximation of matrix functions in Lp

"Vegeu el resum a l'inici del document del fitxer adjunt."

The Analysis of Accounting Multipliers: The NAMEA Approach in the Case of Catalonia

The aim of this paper is the analysis of the Catalan economy (2001) with the use of a National Accounting Matrix with environmental accounts (NAMEA) for the Catalan economy with 2001 data. We will focus on the analysis of the emission multipliers and we will also analyse the impact of a 10% reduction in greenhouse emissions on emission multipliers. This emission-reduction percentage would bring the Catalan economy into compliance with the maximum emissions level allowed by the Kyoto Protocol. We consider three possible scenarios that would allow this goal to be met. First, we will simulate a 10% reduction in regional emissions and a 5% drop in the endogenous income of the multipliers' model (production, factorial and private income). Second, we will simulate a 10% reduction in emissions and a 10% increase in endogenous income. Finally, we will simulate a 10% reduction in emissions and a 5% increase in endogenous income. Additionally, we will analyse the decomposition of the emission multipliers into own effects, open effects and circular effects to capture the different channels of the emission generation process. Keywords: NAMEA, emission multipliers, Kyoto Protocol.

Structural decomposition analysis and input-output subsystems: An application to Spanish CO2 emissions

Analysis of gas emissions by the input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO2 emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 1990 and 2000. Our results show that services increased their CO2 emissions mainly because of a rise in emissions generated by non-services to cover the final demand for services. In all service activities, the decomposed effects show an increase in CO2 emissions due to a decrease in emission coefficients (i.e., emissions per unit of output) compensated by an increase in emissions caused both by the input-output coefficients and the rise in demand for services. Finally, large asymmetries exist not only in the quantitative changes in the CO2 emissions of the various services but also in the decomposed effects of these changes. Keywords: structural decomposition analysis, input-output subsystems, CO2 emissions, service sector.