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Regression Kink With an Unknown Threshold

Journal of business & economic statistics, 2017-04, Vol.35 (2), p.228-240

Hansen, Bruce E.

2017

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Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data

Energy economics, 2023-04, Vol.120, p.106621, Article 106621

2023

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The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch

Journal of business & economic statistics, 2020-01, Vol.38 (1), p.165-182

Lavetti, Kurt

2020

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Stochastic model specification search for Gaussian and partial non-Gaussian state space models

Econometrics, 2010-01, Vol.154 (1), p.85-100

2010

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Efficient Design and Analysis for a Selective Choice Process

Journal of marketing research, 2017-06, Vol.54 (3), p.430-446

2017

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A variable selection method based on Tabu search for logistic regression models

European journal of operational research, 2009-12, Vol.199 (2), p.506-511

2009

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Short-term wind power forecasting using evolutionary algorithms for the automated specification of artificial intelligence models

International journal of forecasting, 2008-10, Vol.24 (4), p.694-709

2008

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Regression density estimation using smooth adaptive Gaussian mixtures

Econometrics, 2009-12, Vol.153 (2), p.155-173

2009

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Factor forecasting using international targeted predictors: The case of German GDP

Economics letters, 2010-05, Vol.107 (2), p.95-98

Schumacher, Christian

2010

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Heterogeneous treatment effects: Instrumental variables without monotonicity?

Econometrics, 2010-04, Vol.155 (2), p.99-116

Klein, Tobias J.

2010

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Variable reduction, sample selection bias and bank retail credit scoring

Journal of empirical finance, 2010-06, Vol.17 (3), p.501-512

2010

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Forecasting crude oil returns in different degrees of ambiguity: Why machine learn better?

Energy economics, 2024-11, Vol.139, p.107867, Article 107867

2024

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Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?

Journal of empirical finance, 2019-12, Vol.54, p.97-117

2019

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Lucky factors

Journal of financial economics, 2021-08, Vol.141 (2), p.413-435

2021

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Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks

Energy economics, 2018-02, Vol.70, p.396-420

2018

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On LASSO for predictive regression

Journal of econometrics, 2022-08, Vol.229 (2), p.322-349

2022

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Forecasting crude oil market volatility using variable selection and common factor

International journal of forecasting, 2023-01, Vol.39 (1), p.486-502

2023

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ECONOMIC PREDICTIONS WITH BIG DATA: THE ILLUSION OF SPARSITY

Econometrica, 2021-09, Vol.89 (5), p.2409-2437

2021

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Carbon prices forecasting in quantiles

Energy economics, 2022-04, Vol.108, p.105862, Article 105862

2022

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Mixed integer second-order cone programming formulations for variable selection in linear regression

European journal of operational research, 2015-12, Vol.247 (3), p.721-731

2015

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Are systemic risk measures effective? Evidence from macroeconomic downside risk prediction

Applied economics letters, 2024-10, Vol.ahead-of-print (ahead-of-print), p.1-8

2024

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A review on variable selection in regression analysis

Econometrics, 2018-12, Vol.6 (4), p.1-27

Desboulets, Loann David Denis

2018

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A generalized ordinal finite mixture regression model for market segmentation

International journal of research in marketing, 2021-12, Vol.38 (4), p.1055-1072

2021

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Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO

International journal of forecasting, 2019-10, Vol.35 (4), p.1533-1547

2019

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Fast sparse regression and classification

International journal of forecasting, 2012-07, Vol.28 (3), p.722-738

Friedman, Jerome H.

2012

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Regression Kink With an Unknown Threshold

Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data

The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch

Stochastic model specification search for Gaussian and partial non-Gaussian state space models

Efficient Design and Analysis for a Selective Choice Process

A variable selection method based on Tabu search for logistic regression models

Short-term wind power forecasting using evolutionary algorithms for the automated specification of artificial intelligence models

Regression density estimation using smooth adaptive Gaussian mixtures

Factor forecasting using international targeted predictors: The case of German GDP

Heterogeneous treatment effects: Instrumental variables without monotonicity?

Variable reduction, sample selection bias and bank retail credit scoring

Forecasting crude oil returns in different degrees of ambiguity: Why machine learn better?

Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?

Lucky factors

Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks

On LASSO for predictive regression

Forecasting crude oil market volatility using variable selection and common factor

ECONOMIC PREDICTIONS WITH BIG DATA: THE ILLUSION OF SPARSITY

Carbon prices forecasting in quantiles

Mixed integer second-order cone programming formulations for variable selection in linear regression

Are systemic risk measures effective? Evidence from macroeconomic downside risk prediction

A review on variable selection in regression analysis

A generalized ordinal finite mixture regression model for market segmentation

Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO

Fast sparse regression and classification

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