Andreea Iluzia Iacob

Evaluating Java performance for linear algebra numerical computations

Abstract In this paper we evaluate the performance of a Java library in the context of designing numerical solutions for linear algebra problems. Nowadays there are a number of libraries like LAPACK or ATLAS available in C or FORTRAN for solving such problems. Java is a relatively new object-oriented language and is almost universally recognized as a very good programming language for writing portable programs. Despite these advantages, it is a common believe that Java still lags behind C/C++ or Fortran performance especially for computational intensive numerical applications. We developed a Java library for matrix computations and show that using a set of optimization techniques Java can achieve performance comparable with other libraries developed in C or Fortran.

Parallel algorithms for large scale econometric models

Abstract In this paper we have developed algorithms to solve macroeconometric models with forward-looking variables based on Newton method for nonlinear systems of equations. The most difficult step for Newton methods represents the resolution of a large linear system for each iteration. Thus, we compare the performances resulted by solving this linear system using two iterative methods and the direct method. We’ve also described an implementation of the parallel versions of such algorithms using a software package. Our experiments confirm that the iterative methods have a low computational complexity and storage requirements, but the parallel versions of direct methods show a superior speedup.

A Multivariate Mathematical Model to Analyze the Market Prices Correlation at Regional Level

In this work is presented the total least squares algorithm and its application in the economic field, whose calculation can be performed using certain software packages. This approach can be also used to analyze the dependence between various economic indicators, especially for the situation in which the direction of the causality between the model variables is unknown. The model is employed for studying the relation between wheat market prices for three Romanian historical regions, which are some of the most important cereal producers for Romania. The final result consists in a unified formula, which provides a global pattern of the national wheat market as a whole.

The Analysis of the Main Macroeconomic Indicators which Characterize the Romanian Health System

Abstract Most Western countries have passed in the last decade of the twentieth century through significant changes in the health system domain, transformations which directly relate to the financial, organizational and regulatory framework. Romania, along with other European countries, joined the trend of transforming the social and health systems. The health sector is involved in one of the most substantial reforms of the entire Romanian society. In this macroeconomic context, a series of specific indicators were used to characterize the health system in Romania. We also realized an econometric analysis of the correlation between the number of physicians, the number of hospitals, beds in hospitals and the number of patients out of hospital using a linear econometric model.

Regression Using Partially Linearized Gaussian Fuzzy Data

In this work is presented a regression model based on partially linearized Gaussian fuzzy numbers. First we define them and we study some properties compared to conventional Gaussian numbers. Second, these numbers are used in a general least squares procedure for fuzzy data. We also give a numerical example in which the applicability of the proposed method is tested.