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A Poisson Ridge Regression Estimator
Månsson, Kristofer; Shukur, Ghazi - Handelns Utredningsinstitut (HUI Research) - 2010
using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson … calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR …
Persistent link: https://www.econbiz.de/10009150729
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Performance of Some Ridge Parameters for Probit Regression: with Application on Swedish Job Search Data
Locking, Håkan; Månsson, Kristofer; Shukur, Ghazi - Handelns Utredningsinstitut (HUI Research) - 2012
performance of these new estimators are judged by calculating the mean square error (MSE) using Monte Carlo simulations. In the …
Persistent link: https://www.econbiz.de/10009645804
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Métodos cuantitativos para un modelo de regresión lineal con multicolinealidad: Aplicación a rendimientos de letras del tesoro
Gómez, Román Salmerón; Martínez, Eduardo Rodríguez - In: Revista de Métodos Cuantitativos para la Economía y … 24 (2017), pp. 169-189
It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained … also shown that regression with orthogonal variables makes sense regardless of the existence of serious multicollinearity …
Persistent link: https://www.econbiz.de/10011995000
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Ridge type shrinkage estimation of seemingly unrelated regressions and analytics of economic and financial data from "Fragile Five" countries
Yüzbaşı, Bahadır; Ahmed, Syed E. - In: Journal of Risk and Financial Management 13 (2020) 6, pp. 1-19
seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the …
Persistent link: https://www.econbiz.de/10012611360
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Extracting relevant predictors of the severity of mental illnesses from clinical information using regularisation regression models
Kaushik, Sakshi; Sabharwal, Alka; Grover, Gurprit - In: Statistics in Transition new series (SiTns) 23 (2022) 2, pp. 129-152
non-parametric random forest algorithm. The multicollinearity is detected based on the variance inflation factor. Owing to … the presence of multicollinearity, regularisation techniques such as ridge regression and extensions of the least absolute …
Persistent link: https://www.econbiz.de/10013444136
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Ridge type shrinkage estimation of seemingly unrelated regressions and analytics of economic and financial data from "Fragile Five" countries
Yüzbaşı, Bahadır; Ahmed, Syed E. - In: Journal of risk and financial management : JRFM 13 (2020) 6/131, pp. 1-19
seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the …
Persistent link: https://www.econbiz.de/10012309109
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Quantitative methods for a linear regression model with multicollinearity : application to yields of treasury bills
Gómez, Román Salmerón; Martínez, Eduardo Rodríguez - In: Revista de métodos cuantitativos para la economía y … 24 (2017), pp. 169-189
It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained … also shown that regression with orthogonal variables makes sense regardless of the existence of serious multicollinearity …
Persistent link: https://www.econbiz.de/10011845497
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Extracting relevant predictors of the severity of mental illnesses from clinical information using regularisation regression models
Kaushik, Sakshi; Sabharwal, Alka; Grover, Gurprit - In: Statistics in transition : an international journal of … 23 (2022) 2, pp. 129-152
non-parametric random forest algorithm. The multicollinearity is detected based on the variance inflation factor. Owing to … the presence of multicollinearity, regularisation techniques such as ridge regression and extensions of the least absolute …
Persistent link: https://www.econbiz.de/10013419432
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Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?
De Mol, Christine; Giannone, Domenico; Reichlin, Lucrezia - 2006
This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...
Persistent link: https://www.econbiz.de/10010295821
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Scandinavian Evidence on Growth and Age Structure
Andersson, Björn - 1998
The age distribution is seldom taken into consideration in macroeconomic, and macro-econometric papers. This in spite of the fact that established economic theories predict that demographic factors will affect the aggregate economy. This paper focuses on economic growth and investigates...
Persistent link: https://www.econbiz.de/10010321758