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Stability of Algorithms in Statistical Modeling

In: Applied Probability Theory - New Perspectives, Recent Advances and Trends

Author

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  • Alexander A. Kronberg
  • Tatiana K. Kronberg

Abstract

In this paper, we investigate algorithms stability for calculation of multidimensional integrals using the statistical modeling methods. We considered issues of the algorithms optimization and we give sufficient conditions for the stability. We apply our approach to both calculation of integral from the regression function and the moments integral calculation. In all our numerical experiences, we used the mt19937 pseudorandom number generator.

Suggested Citation

  • Alexander A. Kronberg & Tatiana K. Kronberg, 2023. "Stability of Algorithms in Statistical Modeling," Chapters, in: Abdo Abou Jaoude (ed.), Applied Probability Theory - New Perspectives, Recent Advances and Trends, IntechOpen.
    • Handle: RePEc:ito:pchaps:284791
    DOI: 10.5772/intechopen.106136
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    More about this item

    Keywords

    statistical modeling; pseudorandom numbers; optimal density; integral estimation; Monte Carlo methods;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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