LIMIT THEOREMS FOR ESTIMATING UNKNOWN PARAMETERS IN SINGLE-TIME AUTOREGRESSION MODELS

Authors

  • Mirzayev Toxirjon Saloxetdinovich NAMANGAN DAVLAT PEDAGOGIKA INSTITUTI
  • Tojiboyeva Tursunxon Shuxratbek qizi NAMANGAN DAVLAT PEDAGOGIKA INSTITUTI

Keywords:

Simultaneous autoregressive model, limit theorem, Wiener process, least squares method, normal distribution law.

Abstract

This paper proposes new ideas for parameter estimation for a simultaneous autoregressive model. The proposed estimates have a simpler limiting distribution than those obtained by the traditional least squares method.

References

Baran. S., Pap. G. Asymptotic inference for a one-dimensional simultaneous autoregressive model // Metrika, 2009. DOI 10.1007/s00184-009-0289-5.

Anderson T.V. On asymptotic distributions of estimates of parameters of stochastic difference Equations // Ann. Math. Statist, 1959. -V.30. -Pp. 676-687.

White, J.S. The limiting distribution of the serial correlation coefficient in the explosive case // Ann. Math. Statist, 1958. -V. 29. -Pp. 1188-1197.

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Published

2025-07-11

Issue

Vol. 2 No. 5.1 (2025): Materials of the Republican Scientific and Practical Conference on the topic "CONCEPTUAL BASIS OF FUNDAMENTAL, PRACTICAL AND INNOVATIVE RESEARCH IN PEDAGOGICAL EDUCATION AND UPbringing TRANSFORMATION" of the Andijan branch of Kokand University. Namangan 2025.

Section

Articles

License

Copyright (c) 2025 Mirzayev Toxirjon Saloxetdinovich, Tojiboyeva Tursunxon Shuxratbek qizi

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

LIMIT THEOREMS FOR ESTIMATING UNKNOWN PARAMETERS IN SINGLE-TIME AUTOREGRESSION MODELS. (2025). Universal International Scientific Journal, 2(5.1), 52-55. https://universaljurnal.uz/index.php/jurnal/article/view/3196