Estimation of Parameters in Regression Analysis Based on QR Decomposition of Rectangular Matrices by Householder Reflections

Authors

  • Oleksandr Dorokhov University of Tartu
  • Lyudmyla Malyarets Kharkiv National University of Economics
  • Dmytro Yevstrat Kharkiv National University of Economics
  • Kadri Ukrainski

DOI:

https://doi.org/10.31449/inf.v46i4.3984

Abstract

An approach to eliminate multicollinearity problems in regression analysis using QR decomposition of rectangular matrices by Householder reflection has been proposed. The reliability of this computational procedure has been proved.Povzetek: Predložen je pristup uklanjanju problema multikolinearnosti u regresijskoj analizi korištenjem QR dekompozicije pravokutnih matrica Householderovom refleksijom. Dokazana je pouzdanost ovog proračunskog postupka.

Author Biographies

Oleksandr Dorokhov, University of Tartu

Ph.D., School of Economics

Lyudmyla Malyarets, Kharkiv National University of Economics

Dr. Sc, Department of Information Systems

Dmytro Yevstrat, Kharkiv National University of Economics

PhD, department of Information Systems

References

Ishikawa, A., Fujimoto, S., Mizuno, T. (2021). Why does production function take the Cobb–Douglas form? Evolutionary and Institutional Economics Review. Vol. 18(1), 79-102.

Yang, Y., Schmidt, P. (2021). An econometric approach to the estimation of multi-level models. Journal of Econometrics. Vol. 220(2), 532-543.

Liu, L., Fan, T. (2021). The Impact of Identity on Satisfaction toward Entrepreneurial Environment: A Case Study. Discrete Dynamics in Nature and Society. Vol. 2021. 1-8.

A. Borisov, I. (2021). Agricultural personnel and rural labour: How is their reproduction related? Journal of New Economy. Vol. 22(3), 161-183.

Varbanova, V., Beutels, P. (2020). Recent quantitative research on determinants of health in high income countries: A scoping review. PLOS ONE. Vol. 15(9), 1-21.

Wang, W., Zhou, Y. (2021). Eigenvector-based sparse canonical correlation analysis: Fast computation for estimation of multiple canonical vectors. Journal of Multivariate Analysis. Vol. 185(C), 30-41.

Cheng, H. (2021). Importance sampling imputation algorithms in quantile regression with their application in CGSS data. Mathematics and Computers in Simulation (MATCOM). Vol. 188(C), 498-508.

Li, T., Song, X., Zhang, Y., Zhu, H., Zhu, Z. (2021). Clusterwise functional linear regression models. Computational Statistics & Data Analysis. Vol. 158(C), 101-112.

Jian, D., Yu, C., Aihua, G., Jingwei, C., Lili, L., Qinling, C., Shujun, L., Qifeng, X. (2020). Potential Trend for Online Shopping Data Based on the Linear Regression and Sentiment Analysis. Mathematical Problems in Engineering. Vol. 2020, 1-11.

Bagnato, L., Punzo, A. (2021). Unconstrained representation of orthogonal matrices with application to common principal components. Computational Statistics. Vol. 36(2), 1177-1195.

Wei, C., Bo, Z. (2021). Controllability of Flow-Conservation Transportation Networks with Fractional-Order Dynamics. Complexity. Vol. 2021, 1-13.

Wireko, F., Barnes, B., Sebil, C., Ackora-Prah, J. (2021). The Eigenspace Spectral Regularization Method for Solving Discrete Ill-Posed Systems. Journal of Applied Mathematics. Vol. 2021, 1-11.

Jiayan, W., Lanlan, G., Zongmin, L., Xueqin, W., Zhengqing, F. (2021). An Efficient Algorithm for Ill-Conditioned Separable Nonlinear Least Squares. Journal of Mathematics. Vol. 2021, 1-8.

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Published

2022-12-15

How to Cite

Dorokhov, O., Malyarets, L., Yevstrat, D., & Ukrainski, K. (2022). Estimation of Parameters in Regression Analysis Based on QR Decomposition of Rectangular Matrices by Householder Reflections. Informatica, 46(4). https://doi.org/10.31449/inf.v46i4.3984

Issue

Vol. 46 No. 4 (2022)

Section

Technical papers

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