Results 121 to 130 of about 10,375 (259)
Distributed k‐WTA Network for Multi‐Manipulator Competition With Experimental Verifications
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT In this article, a new distributed k $k$‐winner‐take‐all (Dk $k$‐WTA) network is designed and used to construct a dynamic allocation scheme for competitive coordination tasks of multiple manipulators as embodied agents. The scheme is constructed based on the following two aspects. On one hand, with reference to a perspective that the Laplacian
Shengkai Sun, Yutong Li, Jianfeng Lv
wiley +1 more source
Economic Record, EarlyView.We study the effects of heat and high temperature shocks on inflation in Australia using monthly, state‐level temperature anomaly data via two stages. In the first stage, we decompose temperature anomalies into orthogonal components using a structural vector autoregression with long‐run restrictions.
Tan Dat Huynh, Mengheng Li
wiley +1 more source
Unraveling authoritarian reform decision‐making: A metacognitive–subcognitive model
American Journal of Political Science, EarlyView.Abstract Recent research indicates that state reforms in East and Southeast Asia have been predominantly top‐down and authoritarian‐led. However, this significant observation implicitly relies on important assumptions about authoritarian decision‐making behavior and psychology that remains understudied.
Eugene Yu Ji
wiley +1 more source
A tutorial for understanding SEM using R: Where do all the numbers come from?
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Structural equation modeling (SEM) is often seen as a complex and difficult method, especially for those who want to understand how the numbers in SEM software output are actually computed. Although many open‐source SEM tools are now available—especially in the R programming environment—looking into their source code to understand the ...
Yves Rosseel, Marc Vidal
wiley +1 more source
Jacobian-Aware Posterior Sampling for Inverse Problems
Diffusion models provide powerful generative priors for solving inverse problems by sampling from a posterior distribution conditioned on corrupted measurements. Existing methods primarily follow two paradigms: direct methods, which approximate the likelihood term, and proximal methods, which incorporate intermediate solutions satisfying measurement ...
Hen, Liav +3 more
openaire +2 more sources
An extension of the basic local independence model to multiple observed classifications
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The basic local independence model (BLIM) is appropriate in situations where populations do not differ in the probabilities of the knowledge states and the probabilities of careless errors and lucky guesses of the items. In some situations, this is not the case. This work introduces the multiple observed classification local independence model
Pasquale Anselmi +8 more
wiley +1 more source
Assessing the role of spatial externalities in the survival of Italian innovative startups
Regional Science Policy &Practice, EarlyView., 2023 Abstract The paper provides novel empirical evidence about the effects of spatial externalities on the survival of innovative startups in Italy. Using geocoded firm‐level data, we build micro‐geographic measures of specialization and diversity that are robust to the modifiable areal unit problem.
Diego Giuliani +4 more
wiley +1 more source
Bias and precision in true‐score estimation
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract We discuss two approaches to estimating the true score from classical test theory, each with a corresponding measure of uncertainty due to measurement error: the classical method with the standard error of measurement (SEM) and Kelley's method with the standard error of estimation (SEE).
L. Andries van der Ark +3 more
wiley +1 more source
New estimation methods for diagnostic classification models
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract This paper introduces a new class of estimators for cognitive diagnosis models (CDMs) based on the Cressie–Read family of ϕ$$ \phi $$‐divergences. Focusing on the loglinear CDM (LCDM), for which joint maximum likelihood estimation (JMLE) has been shown to be consistent, we propose a joint minimum divergence estimation (JMDE) framework.
Elena Castilla
wiley +1 more source
Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
wiley +1 more source