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Notes on approximation of stochastic programming problem
Šmíd, Martin
In stochastic optimization problems, expectation of random function is often being minimized. Since the expectation can rarely be evaluated exactly an approximation has to be done. In the present paper, three types of approximation are dealt with: discretization, Monte Carlo and Quasi Monte Carlo. Convergence rate of the approximation error is evaluated and some upper bounds of the error are given.
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Total cost of a construction - a mathematical model
Bauer, K. ; Lachout, Petr
The paper presents a mathematical model for a total cost of a larger construction, e.g. a factory, a department store, a speed-way, etc. The total cost is divided into several subcosts according to specific features. Each particular subcost is considered to be random by nature, and, consequently, the total cost itself is random in our model. We aim to give a tool convenient for decision making.
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Stochastic optimization problems and dependent data
Kaňková, Vlasta
It is well-known that empirical estimates are usually employed when it is necessary to solve a stochastic decision problem depending on a completely unknown probability measure. The aim of this paper is to recall and summarize some rather new results achieved for dependent data that correspond rather often to economic activities.
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Extended Kalecki-Kaldor model revisited
Kodera, Jan ; Sladký, Karel ; Vošvrda, Miloslav
This contribution is devoted to an extended Kalecki-Kaldor model. Differential equations for the development of the real product (output) and capital stock of the economy are formulated for a given value of the inflation rate. A dynamical model of money market is considered either the LM model or the Fisherian model. Stability and robustness are analysed for the complete model.
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