Results 81 to 90 of about 1,823 (234)
ABSTRACT Repetitive motion planning (RMP) for redundant manipulators with high convergent precision becomes an intense research topic due to its more degrees of freedom. In this paper, a specific zeroing neural dynamics (SZND) model for the RMP is first set up via zeroing neurodynamics.
Ying Kong +3 more
wiley +1 more source
Abstract We estimate the price impact of very nearby concurrently listed properties in the Sydney housing market and assess their competition effects. We apply a hedonic model with spatiotemporal effects regularized via a graph Laplacian prior at the month‐by‐SA2 regional level to seven SA4 subregions of metropolitan Sydney. The model structure enables
Willem P. Sijp, Mengheng Li
wiley +1 more source
Graph‐Laplacian modeling of spatiotemporal effects for house price estimation
Abstract Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input
Willem P Sijp, Marc K. Francke
wiley +1 more source
On the Kronecker Product of Sn Characters
AbstractLet χρ, χλ, χμ be irreducible Sn characters and assume χρ appears in the Kronecker product χλ⊗χμ with maximal first part ρ1. Then ρ1 = |λ∩μ| = ∑min(λi, μi). A similar result holds for the maximal first column. We also give a recursive formula for χλ⊗χμ. As an application, we show that if n = λ1 + μ1 − ρ1, then 〈χλ⊗χμχρ〉sn = 〈χ(λ2, λ3, ...)⊗χ(μ2,
openaire +1 more source
A tutorial for understanding SEM using R: Where do all the numbers come from?
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
Extending reliability to intensive longitudinal data with the Kalman filter
Abstract Reliability is central to how researchers approach measurement in standard, group‐based analyses of single‐time‐point data, yet this critical aspect is often overlooked in the analysis of repeated observations. Since its inception, reliability has been a between‐person concept, but we redevelop this notion for within‐person designs by ...
Michael D. Hunter
wiley +1 more source
Identifying Kronecker product factorizations
21 pages, 13 ...
Voet, Yannis Dirk, De Novellis, Leonardo
openaire +2 more sources
Abstract The social relations model (SRM) is commonly used in psychological research to analyse interdependent data from round‐robin designs, where all members of a group rate each other. Based on the recently suggested social relations confirmatory factor analysis (SR‐CFA), we present general formulas for determining the reliability of composites of ...
Steffen Nestler +2 more
wiley +1 more source
To vary or not to vary: A flexible empirical Bayes factor for testing variance components
Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley +1 more source
Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source

