Results 141 to 150 of about 29,799 (296)

MARS‐Diff: Guarded Residual Diffusion for Leakage‐Disciplined Probabilistic Portfolio‐Loss Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT This paper develops Masked Asset–Regime Scenario Diffusion (MARS‐Diff), a leakage‐disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR‐X) as its anchor, a train‐only masked representation of a high‐dimensional ...
Çağlar Sözen, Mervenur Sözen
wiley   +1 more source

Using recurrent neural network to estimate irreducible stochasticity in human choice behavior

eLife
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others.
Yoav Ger, Moni Shahar, Nitzan Shahar
doaj   +1 more source

Beyond Prediction: Data, Baselines, Explanation, and Causation in Machine Learning for Food Insecurity

Food Safety and Health, EarlyView.
The gains from machine learning in nowcasting and forecasting food insecurity are still small and limited and cannot be observed in all countries. This review summarizes the public resources for data, corrects common misconceptions about model requirements, and establishes baseline requirements, explanations, causal inference, and equity in operational
Shabnam Mehboob, Azman Abdullah, Gunesh Kumar, Samreen Memon, Naila Afghan   +4 more
wiley   +1 more source

Semi-parametric local variable selection under misspecification [PDF]

Local variable selection aims to test for the effect of covariates on an outcome within specific regions. We outline a challenge that arises in the presence of non-linear effects and model misspecification.
Saez, Ignacio, Guindani, Michele, Kseung, Arnold Kisuk, Rossell, David   +3 more
core   +1 more source

Sequential design augmentation with model misspecification

, 2007
In Response Surface Methodology (RSM) one attempts to model some variable of interest, usually as a known function of design variables. Subsequent analysis often indicates a need to move to a new region of interest.
Sutherland, Sindee S.
core  

Case‐Mix Adjustment of Multidimensional Patient‐Reported Outcomes to Assess Hospital Performance

Health Economics, EarlyView.
ABSTRACT Multidimensional patient‐reported outcome measures (PROMs) are increasingly used to compare the performance of health care providers. Meaningful comparisons require the data to be adjusted for differences in case‐mix. The common approach in the literature is to aggregate PROM data into univariate summary scores prior to case‐mix adjustment. In
Nils Gutacker, Yuanyuan Gu
wiley   +1 more source

Misspecified Bayesian Learning by Strategic Players : First-Order Misspecification and Higher-Order Misspecification

We consider strategic players who may have a misspecified view about the world, and investigate their long-run behavior when they learn an unknown state from public signals over time. Our framework is flexible and allows for higher-order misspecification,
Murooka, Takeshi, Yamamoto, Yuichi
core   +1 more source

Minimizing Sensitivity to Model Misspecification

We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax
Stéphane Bonhomme, Martin Weidner
core  

The Structure of Informal Learning in the Workplace—An Experience Sampling Approach

Human Resource Development Quarterly, EarlyView.
ABSTRACT This paper complements retrospective approaches to researching informal learning in the workplace with experience sampling. Since (conscious) informal learning is becoming increasingly important for successfully keeping pace with rapid changes in working environments, a clear understanding of the construct and its precise measurement are ...
Katja Häußermann, Tina Seufert
wiley   +1 more source

Formative and Reflective Measurement Models in Workplace Learning Research: A Critical Review and Guidelines

Human Resource Development Quarterly, EarlyView.
ABSTRACT Quantitative empirical research in workplace learning regularly makes use of measurement instruments that operationalize theoretical constructs. However, in domains related to workplace learning, high levels of measurement model misspecifications—up to 62% of all cases—have been identified.
Josef Guggemos, Michael Goller
wiley   +1 more source