What is it about?
Longitudinal/functional/sequential data are most commonly used in biology, medicine science and finance. This paper proposed a new method/framework to estimate the parameters/coefficients more precisely/efficiently.
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Why is it important?
Improving estimation efficiency for regression coefficients is an important issue in the analysis of longitudinal/functional data, which helps us to find more interesting and significant features in medicine science/biological experiments.
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This page is a summary of: Efficient semiparametric regression for longitudinal data with regularised estimation of error covariance function, Journal of Nonparametric Statistics, August 2019, Taylor & Francis, DOI: 10.1080/10485252.2019.1651853.
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