Fits Piecewise Constant Models with Data-Adaptive Knots
Implements the fused lasso additive model as proposed in Petersen, A., Witten, D., and Simon, N. (2014). Fused Lasso Additive Model. arXiv preprint arXiv:1409.5391.

Rcpp (>= 0.11.6), MASS, graphics, grDevices, stats

Implements the fused lasso additive model as proposed in Petersen, A., Witten, D., and Simon, N. (2015). Fused Lasso Additive Model. To appear in the Journal of Computational and Graphical Statistics.

Implements the fused lasso additive model as proposed in Petersen, A., Witten, D., and Simon, N. (2016). Fused Lasso Additive Model. Journal of Computational and Graphical Statistics, 25(4): 1005-1025.

A generative art system for producing tree-like
images using an L-system to create the structures. The package
includes tools for generating the data structures and visualise
them in a variety of styles.
tibble, dplyr, purrr, tidyr, ggplot2, ggforce, paletteer,
magrittr

tibble, dplyr, purrr, tidyr, ggplot2, ggforce, magrittr

Functional Latent Data Models for Clustering Heterogeneous
Curves ('FLaMingos')
c(person("Faicel", "Chamroukhi", role = c("aut"),
email = "faicel.chamroukhi@unicaen.fr",
comment = c(ORCID = "0000-0002-5894-3103")),
person("Florian", "Lecocq", role = c("aut", "trl", "cre"),
comment = ("R port"),
email = "florian.lecocq@outlook.com"),
person("Marius", "Bartcus", role = c("aut","trl"),
comment = ("R port"),
email = "marius.bartcus@gmail.com"))
Provides a variety of original and flexible user-friendly
statistical latent variable models for the simultaneous clustering and
segmentation of heterogeneous functional data (i.e time series, or more
generally longitudinal data, fitted by unsupervised algorithms, including
EM algorithms. Functional Latent Data Models for Clustering heterogeneous
curves ('FLaMingos') are originally introduced and written in 'Matlab' by
Faicel Chamroukhi
<https://github.com/fchamroukhi?utf8=?&tab=repositories&q=mix&type=public&language=matlab>.
The references are mainly the following ones.
Chamroukhi F. (2010) <https://chamroukhi.com/FChamroukhi-PhD.pdf>.
Chamroukhi F., Same A., Govaert, G. and Aknin P. (2010) <doi:10.1016/j.neucom.2009.12.023>.
Chamroukhi F., Same A., Aknin P. and Govaert G. (2011). <doi:10.1109/IJCNN.2011.6033590>.
Same A., Chamroukhi F., Govaert G. and Aknin, P. (2011) <doi:10.1007/s11634-011-0096-5>.
Chamroukhi F., and Glotin H. (2012) <doi:10.1109/IJCNN.2012.6252818>.
Chamroukhi F., Glotin H. and Same A. (2013) <doi:10.1016/j.neucom.2012.10.030>.
Chamroukhi F. (2015) <https://chamroukhi.com/FChamroukhi-HDR.pdf>.
Chamroukhi F. and Nguyen H-D. (2019) <doi:10.1002/widm.1298>.
flamingos-package.R RcppExports.R utils.R kmeans.R
mkStochastic.R FData.R ParamMixHMM.R ParamMixHMMR.R
ParamMixRHLP.R StatMixHMM.R StatMixHMMR.R StatMixRHLP.R
ModelMixHMMR.R ModelMixHMM.R ModelMixRHLP.R emMixHMM.R
emMixHMMR.R emMixRHLP.R cemMixRHLP.R data-toydataset.R
Faicel Chamroukhi [aut] (<https://orcid.org/0000-0002-5894-3103>),
Florian Lecocq [aut, trl, cre] (R port),
Marius Bartcus [aut, trl] (R port)