Results 51 to 60 of about 77,552 (290)
Market Selection and Learning Under Model Misspecification
Journal of Economic Dynamics and Control, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Giulio Bottazzi +2 more
openaire +3 more sources
Exploring the Impact of Meat Alternative Labeling Regulations on the U.S. Meat Consumption Patterns
Agribusiness, EarlyView.ABSTRACT The global demand for conventional meat continues to rise, but it is also associated with substantial environmental and health challenges. In response, meat alternatives have gained popularity, sparking debates over meat alternative labeling regulations. This study investigates the effects of meat alternative labeling regulations in the United
Jeong Hun Ji, Sang Hyeon Lee
wiley +1 more source
Welfare Cost of Model Uncertainty in a Small Open Economy
Entropy, 2020 This paper extends the canonical small open-economy real-business-cycle model, when considering model uncertainty. Domestic households have multiplier preferences, which leads them to take robust decisions in response to possible model misspecification ...
Jocelyn Tapia Stefanoni
doaj +1 more source
Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]
, 2010 This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Ichimura, H, Lee, S
core +3 more sources
Advanced Intelligent Systems, EarlyView.A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez +4 more
wiley +1 more source
Journal of Statistical Software, 2018 Predictor effect displays, introduced in this article, visualize the response surface of complex regression models by averaging and conditioning, producing a sequence of 2D line graphs, one graph or set of graphs for each predictor in the regression ...
John Fox, Sanford Weisberg
doaj +1 more source
Accounting for animal health in efficiency analysis: An application to Swedish dairy farms
American Journal of Agricultural Economics, EarlyView.Abstract Poor animal health is a central concern in modern livestock production. Despite the necessity to incorporate animal health in efficiency analysis, the theoretical and empirical developments are limited on this subject. This article appropriately characterizes the axiomatic properties of animal health within a production framework.
Frederic Ang +3 more
wiley +1 more source
Food insecurity and unemployment among immigrants in the United States
American Journal of Agricultural Economics, EarlyView.Abstract Immigrants can be more vulnerable to economic downturns and, during periods of economic hardship, more likely to experience food insecurity compared to natives. This study examines the differential effect of the unemployment rate on the probability of being food insecure among diverse groups of immigrant households relative to natives in the ...
Siwen Zhou +3 more
wiley +1 more source
Parameter uncertainties for imperfect surrogate models in the low-noise regime
Machine Learning: Science and TechnologyBayesian regression determines model parameters by minimizing the expected loss, an upper bound to the true generalization error. However, this loss ignores model form error, or misspecification, meaning parameter uncertainties are significantly ...
Thomas D Swinburne, Danny Perez
doaj +1 more source