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Latent variables analysis in person-oriented research [PDF]
Journal for Person-Oriented Research, 2023 In this article, we demonstrate that latent variable analysis can be of great use in person-oriented research. Starting with exploratory factor analysis of metric variables, we present an example of the problems that come with generalization of ...
Alexander von Eye +2 more
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Coding of latent variables in sensory, parietal, and frontal cortices during closed-loop virtual navigation [PDF]
eLife, 2022 We do not understand how neural nodes operate and coordinate within the recurrent action-perception loops that characterize naturalistic self-environment interactions.
Jean-Paul Noel +7 more
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Neural criticality from effective latent variables [PDF]
eLifeObservations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is ‘avalanche criticality’, which has been observed in various systems, including ...
Mia C Morrell +2 more
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A Wilcoxon–Mann–Whitney Test for Latent Variables [PDF]
Frontiers in Psychology, 2021 We propose an extension of the Wilcoxon–Mann–Whitney test to compare two groups when the outcome variable is latent. We empirically demonstrate that the test can have superior power properties relative to tests based on Structural Equation Modeling for a
Heidelinde Dehaene +2 more
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Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables [PDF]
Frontiers in Immunology, 2023 In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge
Alexander B. Brummer +8 more
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A protocol for modelling generalised biological responses using latent variables in structural equation models [PDF]
One Ecosystem, 2021 In this paper, we consider the problem of how to quantitatively characterise the degree to which a study object exhibits a generalised response. By generalised response, we mean a multivariate response where numerous individual properties change in ...
James Grace, Magdalena Steiner
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Nonsparse Learning with Latent Variables [PDF]
Operations Research, 2021 A New Nonsparse Learning Methodology for High-Dimensional Data Analysis Is Coming
Zemin Zheng, Jinchi Lv, Wei Lin 0020
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Dynamic system multivariate calibration based on multirate sampling data [PDF]
Modeling, Identification and Control, 2001 The statistical principal component regression (PCR) and chemometric partial least squares regression (PLSR) algorithms based on latent variables (LV) modeling are effective tools for handling ill-conditioned regression data.
Rolf Ergon, Maths Halstensen
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A didactically motivated PLS prediction algorithm [PDF]
Modeling, Identification and Control, 2001 The intention of this paper is to develop an easily understood PLS prediction algorithm, especially for the control community. The algorithm is based on an explicit latent variables model, and is otherwise a combination of the previously published ...
Rolf Ergon, Kim H. Esbensen
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Latent Variable Autoencoder [PDF]
IEEE Access, 2019 Learning to discover hidden variables from unlabeled data is an important task. Traditional generative methods model the generation process of the observed variables as well as the hidden variables. However, tractable inference and learning on these models requires strong conditional independence assumptions being made among observed and hidden ...
Wenjuan Han, Ge Wang 0005, Kewei Tu
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