The Impact of Uncertainty on Forecasting the US Economy
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley +1 more source
Sketch-based image retrieval via CAT loss with elastic net regularization
Jia Cai, Guanglong Xu, Zhensheng Hu
openalex +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source
Nowcasting World Trade With Machine Learning: A Three‐Step Approach
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn +2 more
wiley +1 more source
This study develops a novel miRNA‐based framework for estimating the time since deposition of semen stains, combining small RNA sequencing with machine learning. Time‐dependent miRNA modules were identified using Mfuzz clustering and WGCNA, followed by a multi‐stage feature selection pipeline that reduced 261 candidate miRNAs to a minimal 7‐miRNA panel.
Meiming Cai +11 more
wiley +1 more source
Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm [PDF]
Vahid Ebrahimi +6 more
openalex +1 more source
Abstract Brain development in preterm infants shows marked heterogeneity, often obscured by group‐level analyses. Between the group‐level and the individual difference, subgroup can model the heterogeneity of early developmental trajectories. To characterize this, we analyzed longitudinal functional connectome data from 90 preterm infants (scanned at ...
Jing Yu +8 more
wiley +1 more source
Research of Magnetic Particle Imaging Reconstruction based on the Elastic Net Regularization
Xiaojun Chen +3 more
openalex +1 more source
A Machine Learning Approach to Assess Differential Item Functioning in Psychometric Questionnaires Using the Elastic Net Regularized Ordinal Logistic Regression in Small Sample Size Groups [PDF]
Vahid Ebrahimi +3 more
openalex +1 more source
The use of edible insects in human food
Abstract The world population is expected to reach approximately 10 billion people by 2050, which will significantly increase global food demand and may lead to agricultural shortages and a higher risk of food insecurity. In this context, this review discusses the potential of insects as alternative sources of animal protein, addressing their ...
Pamela Barroso de Oliveira +5 more
wiley +1 more source

