Ecosyste.ms: Papers
An open API service providing mapping between scientific papers and software projects that are mentioned in them.
All mentions data is based on the CZI Software Mentions dataset.
Projects: cran: mixAK
https://packages.ecosyste.ms/registries/cran.r-project.org/packages/mixAK
Multivariate Normal Mixture Models and Mixtures of Generalized
Linear Mixed Models Including Model Based Clustering
33 versions
Latest release: about 1 year ago
5 dependent packages
1,040 downloads last month
Papers Mentioning mixAK 9
10.1186/1471-2288-13-62
Predicting hemoglobin levels in whole blood donors using transition models and mixed effects modelsCited by: 14
Author(s): Kazem Nasserinejad, Wim de Kort, M. L. Baart, Arnošt Komárek, Joost van Rosmalen, Emmanuel Lesaffre
Software Mentions: 4
Published: over 11 years ago
10.1371/journal.pone.0168838
Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture ModelsCited by: 68
Author(s): Kazem Nasserinejad, Joost van Rosmalen, Wim de Kort, Emmanuel Lesaffre
Software Mentions: 2
Published: almost 8 years ago
10.1002/bimj.201700013
A comparison of group prediction approaches in longitudinal discriminant analysisCited by: 5
Author(s): David Hughes, Riham El Saeiti, Marta García‐Fiñana
Software Mentions: 1
Published: over 7 years ago
10.1111/dom.13552
Personalized risk-based screening for diabetic retinopathy: A multivariate approach versus the use of stratification rulesCited by: 15
Author(s): Marta García‐Fiñana, David Hughes, Christopher P. Cheyne, Deborah Broadbent, Amu Wang, Arnošt Komárek, I M Stratton, Mehrdad Mobayen‐Rahni, Ayesh Alshukri, Jiten Vora, Simon Harding
Software Mentions: 1
Published: about 6 years ago
10.1002/sim.7397
Dynamic classification using credible intervals in longitudinal discriminant analysisCited by: 8
Author(s): David Hughes, Arnošt Komárek, Laura Bonnett, Gabriela Czanner, Marta García‐Fiñana
Software Mentions: 1
Published: over 7 years ago
10.1177/0962280216674496
Dynamic longitudinal discriminant analysis using multiple longitudinal markers of different typesCited by: 18
Author(s): David Hughes, Arnošt Komárek, Gabriela Czanner, Marta García‐Fiñana
Software Mentions: 1
Published: about 8 years ago
10.18632/aging.103623
Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progressionCited by: 10
Author(s): Konstantinos Poulakis, Daniel Ferreira, Joana B. Pereira, Örjan Smedby, Prashanthi Vemuri, Eric Westman
Software Mentions: 1
Published: over 4 years ago
10.16910/jemr.14.3.2
Angular offset distributions during fixation are, more often than not, multimodalCited by: 3
Author(s): Lee Friedman, Dillon Lohr, Timothy Hanson, Oleg V. Komogortsev
Software Mentions: 1
Published: over 3 years ago
10.1186/s12874-017-0415-4
Predicting the multi-domain progression of Parkinson’s disease: a Bayesian multivariate generalized linear mixed-effect modelCited by: 5
Author(s): Ming Wang, Zheng Li, Eun Young Lee, Mechelle M. Lewis, Lijun Zhang, Nicholas W. Sterling, Daymond Wagner, Paul J. Eslinger, Guangwei Du, Xuemei Huang
Software Mentions: 1
Published: about 7 years ago