Results 41 to 50 of about 33,702 (146)
Asymptotic standard errors for reliability coefficients in item response theory
Abstract In a recent review, Liu et al. (Psychological Methods, 2025b) classified reliability coefficients into two types: classical test theory (CTT) reliability and proportional reduction in mean squared error (PRMSE). This article focuses on quantifying the sampling variability of these coefficients under item response theory (IRT) models.
Youjin Sung, Yang Liu
wiley +1 more source
Semiparametric estimation for a class of time-inhomogenous diffusion processes [PDF]
Copyright @ 2009 Institute of Statistical Science, Academia SinicaWe develop two likelihood-based approaches to semiparametrically estimate a class of time-inhomogeneous diffusion processes: log penalized splines (P-splines) and the local log-linear ...
Li, M, Wang, H, Yu, K, Yu, Y
core
Beyond Sporting Talent: Other Determinants of Football Clubs’ Wage Bills
ABSTRACT This article delves into the understanding of how football clubs determine wage bills to compensate talent. Using data from first‐division teams in elite European leagues, we estimate wage models based on indicators of sporting performance, “Elo ratings” as a proxy for clubs’ historical achievements and brand strength, and “media visibility ...
Alice Aguiar‐Noury +1 more
wiley +1 more source
Spatial Correlation Robust Inference with Errors in Location or Distance [PDF]
This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. We investigate the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic ...
Conley, Timothy G., Molinari, Francesca
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Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation
Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo +3 more
wiley +1 more source
ABSTRACT There is an increased proportion of studies using quantile‐based regression methodology (QR) in economics. They offer a robust alternative to classical mean regressions, which can estimate non‐normal variables with distributional heterogeneity in the dependent variable.
Shajara Ul‐Durar +4 more
wiley +1 more source
Econometrics at the Extreme: From Quantile Regression to QFAVAR1
ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source
Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients
ABSTRACT The problem of selecting the smoothing parameter, or bandwidth, for kernel‐based estimators of time‐varying coefficients in linear models with possibly endogenous explanatory variables is considered. We examine automated bandwidth selection by means of cross‐validation, a nonparametric variant of Akaike's information criterion, and bootstrap ...
Charisios Grivas, Zacharias Psaradakis
wiley +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro +2 more
wiley +1 more source
ABSTRACT Expectile is a coherent and elicitable law‐invariant risk measure widely applied in risk management. Existing methods based on iteratively reweighted least squares (IWLS) are not computationally efficient for large‐scale sample sizes. To overcome the issue, we develop a direct nonparametric conditional expectile function estimator by inverting
Feipeng Zhang, Ping‐Shou Zhong
wiley +1 more source

