Výsledky vyhledávání - "Nghiem, Linh H."

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Random effects model-based sufficient dimension reduction for independent clustered data

Sufficient dimension reduction (SDR) is a popular class of regression methods which aim to find a small number of linear combinations of covariates that capture all the information of the responses i.e., a central subspace. The majority of current me

Externí odkaz: http://arxiv.org/abs/2410.09712

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Enhancing Empathic Accuracy: Penalized Functional Alignment Method to Correct Misalignment in Emotional Perception

Autor: Nghiem, Linh H, Cao, Jing, Moon, Chul

Empathic accuracy (EA) is the ability of one person to accurately understand thoughts and feelings of another person, which is crucial for social and psychological interactions. Traditionally, EA is measured by comparing perceivers` real-time ratings

Externí odkaz: http://arxiv.org/abs/2409.05343

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A Linear Errors-in-Variables Model with Unknown Heteroscedastic Measurement Errors

Autor: Nghiem, Linh H., Potgieter, Cornelis J.

In the classic measurement error framework, covariates are contaminated by independent additive noise. This paper considers parameter estimation in such a linear errors-in-variables model where the unknown measurement error distribution is heterosced

Externí odkaz: http://arxiv.org/abs/2310.13874

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Likelihood-based surrogate dimension reduction

Autor: Nghiem, Linh H., Hui, Francis K. C., Mueller, Samuel, Welsh, A. H.

We consider the problem of surrogate sufficient dimension reduction, that is, estimating the central subspace of a regression model, when the covariates are contaminated by measurement error. When no measurement error is present, a likelihood-based d

Externí odkaz: http://arxiv.org/abs/2310.13858

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