SOFTWARE PACKAGE FOR CONSTRUCTING LINEAR REGRESSION models USING THE MIXED ESTIMATION METHOD

В статье описывается программный комплекс, обеспечивающий возможность оценивания параметров линейного регрессионного уравнения методами смешанного оценивания (МСО), наименьших квадратов (МНК) и модулей (МНМ), а также антиробастного оценивания (МАО). Разработанный программный комплекс применен для моделирования объема погрузки основных видов грузов железнодорожным транспортом, в качестве независимых переменных определены объемы погрузки конкурирующими видами транспорта. Это такие факторы, как перевозки автомобильным, морским, трубопроводным и внутренним водным транспортом. Проведён анализ полученных моделей, оценены значения критериев смещения, относительных ошибок аппроксимации, согласованности поведения. The article considers a software package that provides the ability to estimate the parameters of a linear regression equation using mixed estimation (MSO), least squares (OLS) and modules (MCM), as well as anti-blast estimation (MAO). The developed software package was used to model the volume of loading of the main types of cargo by rail, and the competing types of transportation in relation to rail transportation were selected as independent variables. These are such factors as transportation by road, transportation by sea, transportation by pipeline, transportation by inland water transport. The analysis of the obtained models is carried out, the bias criteria, the relative approximation errors, and the generalized behavior consistency criterion (RSPC) are evaluated.

Prior information in econometric real estate appraisal: a mixed estimation procedure

PurposeThe purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.Design/methodology/approachA mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.FindingsThe OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.Originality/valueThe crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.

Axial–equatorial isomerism and semiexperimental equilibrium structures of fluorocyclohexane

Accuracy vs. computational effort: the mixed estimation method provides very accurate semiexperimental equilibrium structures, as illustrated by the subtle differences between axial/equatorial fluorocyclohexane.

The equilibrium molecular structures of 2-deoxyribose and fructose by the semiexperimental mixed estimation method and coupled-cluster computations

The mixed estimation method yields very accurate equilibrium structures, as observed in deoxyribose and fructose.