Statistical applications of optimization methods and mathematical programming

Author:

Manea Daniela-Ioana1,Țiţan Emilia1,Șerban Radu R.2,Mihai Mihaela1

Affiliation:

1. The Bucharest University of Economic Studies , Romania

2. Spiru Haret University , Bucharest

Abstract

Abstract Optimization techniques perform an important role in different domains of statistic. Examples of parameter estimation of different distributions, correlation analysis (parametric and nonparametric), regression analysis, optimal allocation of resources in partial research, exploration of response surfaces, design of experiments, efficiency tests, reliability theory, survival analysis are the most known methods of statistical analysis in which we find optimization techniques. The paper contains a synthetic presentation of the main statistical methods using classical optimization techniques, numerical optimization methods, linear and nonlinear programming, variational calculus techniques. Also, an example of applying the “simplex” algorithm in making a decision to invest an amount on the stock exchange, using a prediction model..

Publisher

Walter de Gruyter GmbH

Reference19 articles.

1. Arthanari, A. T., & Dodge, Y. (1981). Mathematical Programming in Statistics. New York: John Wiley, Interscience Division,.

2. Bertsekas, D. P. (1999). Nonlinear Programming (2nd edition ed.). Belmont, Massachusetts: Athena Scientific.

3. Bickel, P. J., & Doksum, K. (1977). Mathematical Statistics: Basic Ideas and Selected Topics. San Francisco: Holden-Day.

4. Cochran, W. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. Retrieved from https://www.wiley.com/en-us/Sampling+Techniques%2C+3rd+Edition-p-9780471162407

5. Collins, J., & Portnoy, S. (1981). Maximizing the Variance of M-Estimators Using the Generalized Method of Moment Spaces. The Annals of Statistics, 567-577. Retrieved from https://www.jstor.org/stable/2240820?seq=1#page_scan_tab_contents10.1214/aos/1176345460

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