Results 81 to 90 of about 25,451 (177)
Bootstrap Hypothesis Testing [PDF]
This paper surveys bootstrap and Monte Carlo methods for testing hypotheses in econometrics. Several different ways of computing bootstrap P values are discussed, including the double bootstrap and the fast double bootstrap.
James G. MacKinnon
core
ABSTRACT Credit card fraud detection remains a challenging research problem due to the class imbalance issue caused by the rarity of fraudulent transactions. Classical oversampling techniques such as SMOTE, ADASYN and their variants help balance data but do not reflect the nonlinear structure of real‐world fraud, leading to poor generalization.
Sultan Alharbi +2 more
wiley +1 more source
Nonparametric inference for second order stochastic dominance [PDF]
This paper deals with nonparametric inference for second order stochastic dominance of two random variables. If their distribution functions are unknown they have to be inferred from observed realizations. Thus, any results on stochastic dominance are in
Schmid, Friedrich, Trede, Mark
core
Background This study elucidates the intricate relationship between stressful life events and the development of ADHD symptoms in children, acknowledging the considerable variability in individual responses. By examining these differences, we aim to uncover the unique combinations of factors contributing to varying levels of vulnerability and ...
Seung Yun Choi +7 more
wiley +1 more source
A Predictive Model for Intrapartum Cesarean Delivery in Multiparous Women After Active Labor Onset
ABSTRACT Objective Although prediction models for cesarean delivery have been established for nulliparous women, few have been developed for multiparous women, particularly for predicting intrapartum cesarean delivery after the onset of active labor. This study aimed to develop and validate a risk prediction model for intrapartum cesarean delivery in ...
Yanqing Liu +4 more
wiley +1 more source
Gradual Changes in Functional Time Series
ABSTRACT We consider the problem of detecting gradual changes in the sequence of mean functions from a not necessarily stationary functional time series. Our approach is based on the maximum deviation (calculated over a given time interval) between a benchmark function and the mean functions at different time points.
Patrick Bastian, Holger Dette
wiley +1 more source
Proteomic Trajectories of Metabolic and Proteostatic Adaptation During Normothermic Liver Perfusion
ABSTRACT Background Normothermic machine perfusion (NMP) enables metabolic restoration and viability testing of liver grafts, but current viability criteria incompletely predict post‐transplant outcomes. The molecular basis of graft resilience or biliary vulnerability remains unclear. This study aimed to characterise tissue‐level proteomic trajectories
Heithem Jeddou +10 more
wiley +1 more source
Calls to limit immigration are fueled by the belief immigration threatens individual and collective welfare, yet studies on support for restrictionism remain equivocal on this relationship. We explore this relationship and contribute to existing research by measuring group threat as a latent construct based on Blumer's (1958:3) definition of it as an ...
Lynn Hempel, Noel Strapko
wiley +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source
Abstract Purpose To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (131I) therapy in differentiated thyroid carcinoma (DTC) and establish an interpretable predictive framework for clinical decision‐making.
Zhaoxia Luo, Yangyang Lei, Qing Zhang
wiley +1 more source

