An adapted version of the element-wise weighted total least squares method for applications in chemometrics

The Maximum Likelihood PCA (MLPCA) method has been devised in chemometrics as a generalization of the well-known PCA method in order to derive consistent estimators in the presence of errors with known error distribution. For similar reasons, the Total Least Squares (TLS) method has been generalized in the field of computational mathematics and engineering to maintain consistency of the parameter estimates in linear models with measurement errors of known distribution. In a previous paper [M. Schuermans, I. Markovsky, P.D. Wentzell, S. Van Huffel, On the equivalance between total least squares and maximum likelihood PCA, Anal. Chim. Acta, 544 (2005), 254–267], the tight equivalences between MLPCA and Element-wise Weighted TLS (EW-TLS) have been explored. The purpose of this paper is to adapt the EW-TLS method in order to make it useful for problems in chemometrics. We will present a computationally efficient algorithm and compare this algorithm with the standard EW-TLS algorithm and the MLPCA algorithm in computation time and convergence behaviour on chemical data

On errors-in-variables estimation with unknown noise variance ratio

We propose an estimation method for an errors-in-variables model with unknown input and output noise variances. The main assumption that allows identifiability of the model is clustering of the data into two clusters that are distinct in a certain specified sense. We show an application of the proposed method for system identification

Openness, industrialization, and geographic concentration of activities in China

Rapid development, a widening regional gap, and growing concentration of activities have characterized the Chinese economy since the reforms in the late 1970s. This paper examines the spatial disparities of the economic concentration in different stages of development from a geographic approach in the case of China. It aims at offering empirical supports on (1) how concentrated the economic activities are; (2) what factors determine the economic concentration; and (3) whether this concentration differs in the coastal and inland regions. The results show that the high-technology industries highly concentrate in the coastal provinces. The limited diffusion of the labor intensive activities within the coastal region does not significantly modify the major trend of the location and specialization of the industries in the inland region, and does not contribute to narrowing the regional disparities. The paper argues that in order to stimulate the geographic diffusion of economic activities to the inland region, it is important to appropriately alleviate internal migration control, reduce unnecessary state intervention, and further encourage domestic market integration.Economic Theory&Research,Industrial Management,Water and Industry,General Manufacturing,Environmental Economics&Policies

State space description of national economies: the V4 countries

We present a new approach to description of national economies. For this we use the state space viewpoint, which is used mostly in the theory of dynamical systems and in the control theory. Gross domestic product, inflation, and unemployment rates are taken as state variables. We demonstrate that for the considered period of time the phase trajectory of each of the V4 countries (Slovak Republic, Czech Republic, Hungary, and Poland) lies approximately in one plane, so that the economic development of each country can be assocated with a corresponding plane in the state space. The suggested approach opens a way to a new set of economic indicators (for example, normal vectors of national economies, various plane slopes, 2D angles between the planes corresponding to different economies, etc.). The tool used for computations is orthogonal regression (alias orthogonal distance regression, alias total least squares method), and we also give general arguments for using orthogonal regression instead of the classical regression based on the least squares method. A MATLAB routine for fitting 3D data to lines and planes in 3D is provided.Comment: 13 pages, 18 figure

On weighted structured total least squares

In this contribution we extend the result of (Markovsky et. al, SIAM J. of Matrix Anal. and Appl., 2005) to the case of weighted cost function. It is shown that the computational complexity of the proposed algorithm is preserved linear in the sample size when the weight matrix is banded with bandwidth that is independent of the sample size