Estimating the population prevalence and force of infection directly from antibody titres

DOI10.1177/1471082X12457495WikidataQ56880798 ScholiaQ56880798MaRDI QIDQ4970966

No author found.

Publication date: 8 October 2020

Published in: Statistical Modelling (Search for Journal in Brave)

zbMATH Keywords

prevalencemixture modelserological dataforce of infectiontest misclassification

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• FITPACK

Cites Work

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• Medical applications of finite mixture models
• On the asymptotic normality of statistics with estimated parameters
• Direct generalized additive modeling with penalized likelihood.
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
• Asymptotic properties of penalized spline estimators
• Statistical analysis of finite mixture distributions
• Resampling Inference With Complex Survey Data
• Finite mixture models
• Recent Developments in Computer-Assisted Analysis of Mixtures

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