ArticleComputational statistics & data analysis2017
A note on modeling sparse exponential-family functional response curves.
Article in Computational statistics & data analysis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Functional quantile principal component analysis.Biostatistics (Oxford, England) · 2025Article
- Functional Multivariable Logistic Regression With an Application to HIV Viral Suppression Prediction.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Functional principal component based landmark analysis for the effects of longitudinal cholesterol profiles on the risk of coronary heart disease.Statistics in medicine · 2021Article
- Nonnegative decomposition of functional count data.Biometrics · 2020Article
- Registration for exponential family functional data.Biometrics · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Non-Gaussian functional data are considered and modeling through functional principal components analysis (FPCA) is discussed. The direct extension of popular FPCA techniques to the generalized case incorrectly uses a marginal mean estimate for a model that has an inherently conditional interpretation, and thus leads to biased estimates of population and subject-level effects. The methods proposed address this shortcoming by using either a two-stage or joint estimation strategy. The performance of all methods is compared numerically in simulations. An application to ambulatory heart rate monitoring is used to further illustrate the distinctions between approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.