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pro vyhledávání: '"Gómez, Román Salmerón"'
The residualization procedure has been applied in many different fields to estimate models with multicollinearity. However, there exists a lack of understanding of this methodology and some authors discourage its use. This paper aims to contribute to
Externí odkaz:
http://arxiv.org/abs/2410.17680
When the regressors of a econometric linear model are nonorthogonal, it is well known that their estimation by ordinary least squares can present various problems that discourage the use of this model. The ridge regression is the most commonly used a
Externí odkaz:
http://arxiv.org/abs/2407.02583
The paper analyzes how the enlarging of the sample affects to the mitigation of collinearity concluding that it may mitigate the consequences of collinearity related to statistical analysis but not necessarily the numerical instability. The problem t
Externí odkaz:
http://arxiv.org/abs/2407.01172
This paper analyzes the estimation of econometric models by penalizing the sum of squares of the residuals with a factor that makes the model estimates approximate those that would be obtained when considering the possible simple regressions between
Externí odkaz:
http://arxiv.org/abs/2405.05644
Carbon dioxide (CO2) emissions have emerged as a critical issue with profound impacts on the environment, human health, and the global economy. The steady increase in atmospheric CO2 levels, largely due to human activities such as burning fossil fuel
Externí odkaz:
http://arxiv.org/abs/2403.00653
Multicollinearity produces an inflation in the variance of the Ordinary Least Squares estimators due to the correlation between two or more independent variables (including the constant term). A widely applied solution is to estimate with penalized e
Externí odkaz:
http://arxiv.org/abs/2104.14423
This paper analyzes the diagnostic of near multicollinearity in a multiple linear regression from auxiliary centered regressions (with intercept) and non-centered (without intercept). From these auxiliary regression, the centered and non-centered Var
Externí odkaz:
http://arxiv.org/abs/1905.12293
Akademický článek
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Publikováno v:
Computational Statistics; Jun2021, Vol. 36 Issue 2, p1011-1029, 19p
It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained by using the Ordinary Least Squares (OLS) method are unstable. As a solution to this situation, in this paper we present the raise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1687::a22c1c0bdcb80ba7d6a99334037f3e14
https://hdl.handle.net/10419/195386
https://hdl.handle.net/10419/195386