A New Method For Point Estimating Parameters Of Simple Regression

Mikheev A.V., Kazakov B.N.
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A new method is described for finding parameters of univariate regression model: the greatest cosine method. Implementation of the method involves division of regression model parameters into two groups. The first group of parameters responsible for the angle between the experimental data vector and the regression model vector are defined by the maximum of the cosine of the angle between these vectors. The second group includes the scale factor. It is determined by means of “straightening” the relationship between the experimental data vector and the regression model vector. The interrelation of the greatest cosine method with the method of least squares is examined. Efficiency of the method is illustrated by examples.

Keywords: simple regression, point estimation, method of least squares, two-exponential luminescence decay, boiling point of water, electrical resistivity, Bloch–Gruneisen function
Citation in English: Mikheev A.V., Kazakov B.N. A New Method For Point Estimating Parameters Of Simple Regression // Computer Research and Modeling, 2014, vol. 6, no. 1, pp. 57-77
Citation in English: Mikheev A.V., Kazakov B.N. A New Method For Point Estimating Parameters Of Simple Regression // Computer Research and Modeling, 2014, vol. 6, no. 1, pp. 57-77
DOI: 10.20537/2076-7633-2014-6-1-57-77
URL: http://crm-en.ics.org.ru/journal/article/2117/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.
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  • A. V. Mikheev, B. N. Kazakov. Role of the stimulated radiation of Yb3+ ions in the formation of luminescence of the Y0.8Yb0.2F3:Tm3+ solid solution. // JETP Letters. — 2015. — V. 102, no. 5. — P. 279. DOI: 10.1134/S0021364015170087
  • A.V. Mikheev, B.N. Kazakov. Correlation analysis of spectroscopic data. // Journal of Luminescence. — 2017. — V. 184. — P. 117. DOI: 10.1016/j.jlumin.2016.12.019
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