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 models
Cited 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 Models
Cited 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 analysis
Cited by: 5
Author(s): David Hughes, Riham El Saeiti, Marta García‐Fiñana
Software Mentions: 1
Published: about 7 years ago

10.1111/dom.13552

Personalized risk-based screening for diabetic retinopathy: A multivariate approach versus the use of stratification rules
Cited 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 analysis
Cited 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 types
Cited 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 progression
Cited 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, multimodal
Cited 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 model
Cited 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