SVIBOR - Project code: 2-06-233

MINISTRY OF SCIENCE AND TECHNOLOGY

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SVIBOR

SVIBOR - Collecting Data on Projects in Croatia

Project code: 2-06-233


COMPUTER INTENSIVE AND ROBUST METHODS FOR DATA ANALYSIS


Main researcher: LUŽAR, VESNA (26962)


Assistants
Type of research: developmental
Duration from: 01/01/91. to 12/31/93.
Papers on project (total): 34
Papers on project quoted in Current Contents: 1
Institution name: Institut za medicinska istraživanja i medicinu rada, Zagreb (22)
Department/Institute: Department for Applied Mathematics
Address: Zagreb, Unska 3
City: 10000 - Zagreb, Croatia
Communication
Phone: 385 (41) 510-099
Phone: 385 (41) 278-963
Fax: 385 (41) 278-908
E-mail: vluzar@public.srce.hr
Summary: Because assumptions underlying standard methods for data analysis are in many research studies not satisfied, development of robust methods, less sensitive to departures from these assumptions, are of considerable importance for multivariate data analysis and statistics. Today's computing power allows for development and application of special computationally intensive methods, particularly useful where classical methods are unavailable or intractable. In this project, a class of robust methods has been developed. For some of the methods, comparison studies with the classical models have been performed. Also, three new distance measures have been proposed. The problem of estimating biases of the ordered characteristic roots of a random covariance matrix is reduced to the computation of a definite multidimensional integral. Thus, it has been approached by different simulation and variance reduction techniques. In particular, the importance sampling method has been applied. Different methods have been compared in terms of efficiency, defined as variance ratio. The two-dimensional symetric interval eigenvalue problem has been solved, and the results were used to define interval Jacobi method. Numerical stability of the method was investigated. In the study of Malecot's isolation by distance model, a novel table of 'critical' values of Malecot's parameter "b" was introduced, and a simulation study for analysing the power of the quadratic assignment procedure was designed and developed. Computationally intensive and other methods for data analysis have been applied in (1) industrial statistics: for predicting performance of a aeroengine, for analysing traffic, car kinematics and pollution in urban areas, in time series analysis of air quality data; (2) in citation history analysis; (3) in biostatistics: for studying middle Dalmatian population system by Malecot's isolation by distance model, and for histological reclassification of chronic viral hepatitis.

Keywords: Multivariate methods, computationally intensive methods, characteristic roots, simulation, importance sampling method, applied industrial statistics, eigenvalues, Jacobi method, Malecot's isolation by distance model, interval arithmetics

Research goals: Main objectives of the project are: (1) Development of algorithms for data analysis, that are robust to the departures from the assumptions set by the classical models; (2) Comparison of proposed models with the classical; (3) Development and application of simulation and related methods, such as the importance sampling method for the computation of multidimensional statistical integrals; (4) Development of exact bounds for eigenvalues of a two-dimensional interval symmetric matrix; (5) Numerical investigation on real matrices of numerical stability of the Jacobi method; (6) Application of the above models and other methods for data analysis and statistics to various problems in industry (quality improvement), biomedicine and science, in general; (7) To improve the collaboration with engineers, researchers, business managers, medical and other professionals, in performing research studies, applying sound statistical principles, appropriate statistical methods in conjunction with their new responsibilities as managers of an emerging market society; (8) Software development for (1)-(6).

COOPERATION - INSTITUTIONS


  1. Name of institution: Istituto Motori, CNR
    Type of institution: State institute
    Type of cooperation: Joint project
    City: 80125 - Napoli, Italy

  2. Name of institution: Universita degli Studi di Venezia, Facolta di Economia e Commercio, Laboratorio di Statistica
    Type of institution: University/Faculty
    Type of cooperation: Occasional exchange of experts
    City: 30123 - Venezia, Italy

  3. Name of institution: The American University, Department of Mathematics and Statistics
    Type of institution: University/Faculty
    Type of cooperation: Occasional exchange of experts
    City: 20016 - Washington, USA
Other information about the project.
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