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Iassopack : model selection and prediction with regularized regression in stata
Ahrens, Achim; Hansen, Christian Bailey; Schaffer, Mark E. - 2019
This article introduces lassopack, a suite of programs for regularized regression in Stata. lassopack implements lasso …, square-root lasso, elastic net, ridge regression, adaptive lasso and post-estimation OLS. The methods are suitable for the … (implemented in lasso2), K-fold cross-validation and h-step ahead rolling cross-validation for cross-section, panel and time …
Persistent link: https://www.econbiz.de/10011972491
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Measuring financial wellbeing with self-reported and bank-record data
Comerton-Forde, Carole; Haisken-DeNew, John P.; … - 2020
This study develops multi-item scales of the financial wellbeing of customers of a major Australian bank using self-reported survey data that are matched with the customers' financial records. Using Item Response Theory (IRT) models, the study develops: First a Reported Financial Wellbeing Scale...
Persistent link: https://www.econbiz.de/10012316410
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Machine learning estimation of heterogeneous causal effects : empirical Monte Carlo evidence
Knaus, Michael C.; Lechner, Michael; Strittmatter, Anthony - 2018
We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data generation processes (DGPs) based on actual data. We consider 24...
Persistent link: https://www.econbiz.de/10011958919
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Machine learning and multiple abortions
Kumar, Pradeep; Nicodemo, Catia; Oreffice, Sonia; … - 2024
This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient …
Persistent link: https://www.econbiz.de/10014545133
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Fused LASSO as non-crossing quantile regression
Szendrei, Tibor; Bhattacharjee, Arnab; Schaffer, Mark E. - 2024
Quantile crossing has been a challenge for quantile regression, leading to research in how to obtain monotonically increasing quantile estimates. While important contributions, these papers do not provide insight into how enforcing monotonicity influences the estimated coefficients. This paper...
Persistent link: https://www.econbiz.de/10014582290
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Biological age and predicting future health care utilisation
Davillas, Apostolos; Jones, Andrew M. - 2024
collected 5-12 years from baseline. Using least absolute shrinkage and selection operator (LASSO) regression analyses and …
Persistent link: https://www.econbiz.de/10014584339