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Econometric and Environmental Factors Assessment of Enterprise Accounts Payable
Kadochnikova E.I., Zulfakarova L.F., Rahimov F.K.
multiple regression depending on its financial indicators by considering the environmental concerns
Towards sophisticated decision models: Nonadditive robust ordinal regression for preference modeling
Beliakov G., Wu J.-Z., Divakov D.
by using multiple goal linear programming technique. The results show that the k
Statistics and econometrics from the point of view methodology mathematics
Kapustina T., Popyrin A., Savina L.
technologies (EXCEL, Mathematica) are discussed. The example of 2 variants of linear (4-factor) multiple
Econometric Assessment of Sustainable Development Using Commercial Organization Fixed Assets Efficiency
Kadochnikova E.I., Anoshina D.A., Suycheva D.T.
and productive land are important. The authors have constructed a linear model of capital productivity multiple
Shareholder value of the company and financial statements: Econometric estimation of value creation drivers
Kadochnikova E., Usanova D., Zulfakarova L., Drozdova D.
linear multiple regression model and classical least squares methods has been used. The results depict
Analysis of the employee commitment and supply chain integration effects on industrial enterprise
Kulikova L.I., Sungatullina L.B., Sabirova A.I.
based on the multiple regression model and evaluation of the optimal payment times based on a dynamic
Применение модели множественной линейной регрессии для анализа изменения валового регионального продукта в зависимости от объемов собственных и заемных средств малого и среднего бизнеса
Виноградова, Арина Сергеевна, Ерохин, Артем Сергеевич, Тарапкина, Светлана Евгеньевна
This article discusses the application of the method of multiple linear regression to analyze
Прогнозирование цен на недвижимость с помощью множественной линейной регрессии
Суровцев, А. И., Хорошко, К. Н.
Forecasting real estate prices using multiple linear regression
Econometric estimation of economic growth by purchasing management: Neovlassical models to the analysis of qualitative changes
Kadochnikova E., Zulfakarova L., Drozdova D., Salaudiyevich A.
on the sources of regional economic growth by purchasing management. Using linear regression models, a sample
On linear regression and other advanced algorithms for electrical load forecast using weather and time data
Khadiev K., Safina L.
models are considered. These are Linear Regression, Decision Tree, Random Forest and Gradient Tree

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