Examples of using Linear regression model in English and their translations into Russian
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Application of multivariate linear regression models in the economy.
In the waste management sector, one Party reported the use of a linear regression model.
The better the fit of the linear regression model, the closer R2 is to 1.
A linear regression model is used, controlling for the fertility rate, country income level and urbanisation.
In this article two methods of construction linear regression models are considered.
We consider linear regression model with continuous time and strongly dependent stationary Gaussian random noise.
The course assumes familiarity with the linear regression model, but is open to a broad audience.
However, in this case,we can reparameterize our theoretical model so that we end up with a linear regression model.
Application of the linear regression model developed to resolve C4-MV repairs;
Fast estimation of parameters is achieved with introduction of additional filtered linear regression models for each parameter of the signal.
Therefore, the C4-CPHO linear regression model has been reapplied to all claims that were reported in instalments two through seven that contained C4-CPHO losses.
Models(26) and(28) have the advantage of being linear regression models whereas(30) is nonlinear.
Linear regression model, maximal residuals, weak convergence, Gaussian stationary noise, variance and the second spectral moment estimators, estimator consistency.
The results of the previous period experiments with the Markov-modulated linear regression model were presented at the conference Applied Simulation.
A linear regression model was developed from the sample results and used to predict the missing monthly salaries for the claim population. Fifth Report, para.
It has novelty and relevance, because it has no analogues andreproduces a new complex approach in the applied use of the multifactorial linear regression model.
Unfortunately,(22) is a nonlinear regression model whereas the earlier log-log andsemilog models were linear regression models.
With regard to the methodology used to estimate the emission reduction potential of the identified measures,Argentina reported the use of a linear regression model, and Armenia reported the use of a methodology which reflected the IPCC Guidelines source categories.
Unfortunately,(30) is a nonlinear regression model whereas the earlier translog andsemilog quadratic models were linear regression models.
In the light of the external valuation methods used successfully to resolve large numbers of C1-Money andC4-CPHO losses, the Panel adopted a linear regression model to assist with the valuation of recommended amounts for C4-MV repair losses with amounts claimed in excess of US$500.
For linear regression model the conditions of weak convergence of normalized extreme residuals to double exponent curve are obtained which follows from the assumption of normality of random noise.
The results of the previous period experiments with the Markov-modulated linear regression model were presented at the conference Applied Simulation and Modelling(ASM2018), which.
For example, the simplest linear regression models assume a linear relationship between the expected value of Y(the response variable to be predicted) and each independent variable when the other independent variables are held fixed.
Thus, in its second instalment, with developmental assistance from statistical experts and based on a data-set consisting of 7,343 representative claims with C1-Money losses andbased on standard statistical practice, the Panel concluded that a standard linear regression model should be used for the valuation of all C1-Money losses.
However, without looking at residuals, the linear regression model(34) will be much easier to implement than the nonlinear model(32), especially for large data sets.
On the basis of nonlinear regression models, a generalized linear regression model was created for each of these functions, which allowed developing a program using three-dimensional variables and developing a test of a number of statistical hypotheses, in particular, the adequacy of the regression model, the importance of regression coefficients and the practical significance of the regression model. .
In the light of the external valuation methods used successfully toresolve large numbers of C1-Money and C4-CPHO losses, a linear regression model was used to assist with the valuation of recommended amounts for C4-MV repair losses meeting electronic proof of ownership and with amounts claimed for repairs in excess of US$500.
The results of the previous period experiments with the Markov-modulated linear regression model were presented at the conference Applied Simulation and Modelling(ASM2018), which was held in Paris, France, on April 13-15:"Markov-Modulated Linear Regression: a case study of coaches' delay time.
The role of foreign stock market in the financial support of enterprises of the agricultural sector of Ukraine was evaluated on the basis of comparison with the long-term concessional credits and building a linear regression model, which showed a statistical dependency of the annual volume of gross agricultural production volume to the volume of raised funds by placing shares and Eurobonds in this market for the preceding year(i.e. with a 1-year lag).
Consider classical linear multiple regression model.