Una aproximación de la variable aleatoria a procesos de toma de decisión que implican condiciones de riesgo e incertidumbre (An Approximation of the Random Variable to Making Processes Decisions that Involve Risk and Uncertainty Conditions)

2012 ◽  
Author(s):  
Diego Cardona ◽  
Miller Rivera ◽  
Jesus Romero
Keyword(s):  
Random Variable ◽  
Risk And Uncertainty

Generation of Correlated Logistic-Normal Random Variates for Medical Decision Trees

1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark
Keyword(s):  
Monte Carlo ◽  
Decision Trees ◽  
Computer Algebra ◽  
Taylor Series ◽  
Computer Algebra System ◽  
Random Variable ◽  
Monte Carlo Analysis ◽  
Normal Random Variable ◽  
Medical Decision ◽  
Theoretical Results

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.

OPTIMIZATION OF MARKOV SYSTEMS OF QUEUEING WITH WAITING TIME IN THE MATLAB SYSTEM

2017 ◽  
pp. 39-47
Author(s):  
Viktor Afonin ◽  
Vladimir Valer'evich Nikulin
Keyword(s):  
Queueing System ◽  
Queueing Systems ◽  
Random Variable ◽  
Model Systems ◽  
Queuing Systems ◽  
Input Flow ◽  
Continuous Random Variable ◽  
Input Stream ◽  
Time Intervals ◽  
Markov Systems

The article focuses on attempt to optimize two well-known Markov systems of queueing: a multichannel queueing system with finite storage, and a multichannel queueing system with limited queue time. In the Markov queuing systems, the intensity of the input stream of requests (requirements, calls, customers, demands) is subject to the Poisson law of the probability distribution of the number of applications in the stream; the intensity of service, as well as the intensity of leaving the application queue is subject to exponential distribution. In a Poisson flow, the time intervals between requirements are subject to the exponential law of a continuous random variable. In the context of Markov queueing systems, there have been obtained significant results, which are expressed in the form of analytical dependencies. These dependencies are used for setting up and numerical solution of the problem stated. The probability of failure in service is taken as a task function; it should be minimized and depends on the intensity of input flow of requests, on the intensity of service, and on the intensity of requests leaving the queue. This, in turn, allows to calculate the maximum relative throughput of a given queuing system. The mentioned algorithm was realized in MATLAB system. The results obtained in the form of descriptive algorithms can be used for testing queueing model systems during peak (unchanged) loads.

Risk and uncertainty in applied problems of oil and gas economy

2019 ◽  
pp. 30-33
Author(s):  
A.F. Andreev ◽  
◽  
E.V. Burykina ◽  
G.N. Buliskeriya ◽  
◽  
...  
Keyword(s):  
Oil And Gas ◽  
Risk And Uncertainty

Project portfolio valuation using real options

2020 ◽  
Vol 13 (2) ◽  
pp. 126-146
Author(s):  
A.B. Lanchakov ◽  
S.A. Filin ◽  
A.Zh. Yakushev
Keyword(s):  
Real Options ◽  
Real Option ◽  
Project Portfolio ◽  
Risk And Uncertainty ◽  
Expected Effect ◽  
Investment Projects ◽  
Financial Options ◽  
Portfolio Efficiency ◽  
The Face ◽  
Effective Development

Subject. The article analyzes the expected effect of a portfolio of projects in the face of risk and uncertainty, when using real options. Objectives. The purpose is to offer a more objective formula to assess the expected impact of a portfolio of projects for real investment objects under risk and uncertainty, using real options, and provide recommendations for improving the portfolio efficiency. Methods. The study draws on methods of real options and evaluation of investment projects through the real option value, the cash flow discounting method, synthesis, and mathematical modeling. Results. We systematized the main types of real options and developed a formula for calculating the expected effect of project portfolio implementation. The said formula shows that considering the additional long-term costs embedded in a portfolio of real options, which are associated with the use of these real options, and, therefore, reducing the overall risk of projects and the entire portfolio, permit to improve the objectivity of such calculations. Conclusions. When analyzing real options that have real assets as underlying instruments, it is often impossible to apply the computational formulae for financial options, as they differ significantly. The systematization of the main types of real options helps expand the range of application of management solutions. The offered formula enables to improve the efficiency of project insurance under risk and uncertainty and to use additional opportunities for effective development of the company.

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