Results 21 to 30 of about 7,218 (105)
Testing Mean Stability of Heteroskedastic Time Series
Journal of Time Series Analysis, Volume 47, Issue 1, Page 182-200, January 2026.ABSTRACT Time series models are often fitted to the data without preliminary checks for stability of the mean and variance, conditions that may not hold in much economic and financial data, particularly over long periods. Ignoring such shifts may result in fitting models with spurious dynamics that lead to unsupported and controversial conclusions ...
Violetta Dalla +2 more
wiley +1 more source
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
, 2019 We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization of the Heckman selection model that accommodates much richer patterns of heterogeneity in the selection process and effect of the ...
Chernozhukov, Victor +2 more
core +1 more source
Bayesian Nonparametric Sensitivity Analysis of Multiple Test Procedures Under Dependence
Biometrical Journal, Volume 67, Issue 6, December 2025.ABSTRACT This paper introduces a sensitivity analysis method for multiple testing procedures (MTPs) using marginal p$p$‐values. The method is based on the Dirichlet process (DP) prior distribution, specified to support the entire space of MTPs, where each MTP controls either the family‐wise error rate (FWER) or the false discovery rate (FDR) under ...
George Karabatsos
wiley +1 more source
Estimating a Signal In the Presence of an Unknown Background
, 2012 We describe a method for fitting distributions to data which only requires knowledge of the parametric form of either the signal or the background but not both. The unknown distribution is fit using a non-parametric kernel density estimator.
López, Angel M., Rolke, Wolfgang A.
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A class of directed acyclic graphs with mixed data types in mediation analysis
Canadian Journal of Statistics, Volume 53, Issue 4, December 2025.Abstract We propose a unified class of generalized structural equation models (GSEMs) with data of mixed types in mediation analysis, including continuous, categorical, and count variables. Such models extend substantially the classical linear structural equation model to accommodate many data types arising from the application of mediation analysis ...
Wei Hao, Canyi Chen, Peter X.‐K. Song
wiley +1 more source
Optimal No-regret Learning in Repeated First-price Auctions
, 2020 We study online learning in repeated first-price auctions with censored feedback, where a bidder, only observing the winning bid at the end of each auction, learns to adaptively bid in order to maximize her cumulative payoff.
Han, Yanjun +2 more
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A New Version of Kumaraswamy Distribution With Estimations and Applications
Engineering Reports, Volume 7, Issue 12, December 2025.In this article, the unit interval in the Kumaraswamy distribution is extended to double‐bounded interval. The proposed model is constituted by the transformation of a logistic random variable with a power parameter, flexible enough to fit a wide range of real‐life scenarios involving risk evaluation.
Sadaf Khan +3 more
wiley +1 more source
IEEJ Transactions on Electrical and Electronic Engineering, Volume 20, Issue 12, Page 2100-2109, December 2025.This study proposes statistical models for mitigating the risks associated with variable power sources by establishing a headroom to absorb prediction errors when PV power plants perform day‐ahead planning without the use of battery systems or intraday market procurement. Specifically, three models are proposed in this study.
Jindan Cui +3 more
wiley +1 more source
AeroGP: Machine Learning How Aerosols Impact Regional Climate
Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.Abstract Aerosol particles from both natural and anthropogenic sources play a critical role in the Earth's climate by interacting with solar radiation and clouds. Anthropogenic aerosol and precursor emissions have historically exerted a global cooling effect, which has partially offset the warming from concurrent greenhouse gas emissions.
Maura Dewey +9 more
wiley +1 more source
Inference on Breakdown Frontiers
, 2019 Given a set of baseline assumptions, a breakdown frontier is the boundary between the set of assumptions which lead to a specific conclusion and those which do not. In a potential outcomes model with a binary treatment, we consider two conclusions: First,
Masten, Matthew A., Poirier, Alexandre
core +1 more source