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06/26/2023
Nonlinear Functional Principal Component Analysis Using Neural Networks
Functional principal component analysis (FPCA) is an important technique...
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01/15/2023
Kernel partial least squares regression for functional nonlinear models
Functional regression is very crucial in functional data analysis and a ...
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10/11/2022
An anti-confounding method for estimating optimal regime in a survival context using instrumental variable
There is extensive literature on the estimation of the optimal individua...
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06/09/2022
Locally sparse estimator of generalized varying coefficient model for asynchronous longitudinal data
In longitudinal study, it is common that response and covariate are not ...
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05/30/2022
Partial Replacement Imputation Estimation Method for Complex Missing Covariates in Additive Partially Linear Models
Missing data is a common problem in clinical data collection, which caus...
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09/16/2021
Sparse logistic functional principal component analysis for binary data
Functional binary datasets occur frequently in real practice, whereas di...
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06/16/2021
Projective Resampling Imputation Mean Estimation Method for Missing Covariates Problem
Missing data is a common problem in clinical data collection, which caus...
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05/03/2021
Model Averaging by Cross-validation for Partially Linear Functional Additive Models
We consider averaging a number of candidate models to produce a predicti...
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02/02/2021
Robust Functional Principal Component Analysis for Non-Gaussian Continuous Data to Analyze Physical Activity Data Generated by Accelerometers
Motivated by energy expenditure observations measured by wearable device...
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02/01/2021