Title: Highlight, Annotate, and Format your R Source Code
Description: Facilitates easier formatting and highlighting of R
source code in a R Markdown-based presentation. The main goal of the
package is to allow users to preserve their code creation process
within code chunks, then to specify formatting details for the source
code, such as highlighting of particular syntactical elements.
Imports: dplyr, evaluate, ggplot2, glue, knitr, magrittr, purrr,
Suggests: learnr, rstudioapi, shiny, testthat (>= 2.1.0)

Title: Fits Piecewise Constant Models with Data-Adaptive Knots
Description: 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.

Packaged: 2015-06-24 17:50:15 UTC; ashleypetersen

Imports: Rcpp (>= 0.11.6), MASS, graphics, grDevices, stats
Packaged: 2015-07-26 21:28:49 UTC; ashleypetersen

Description: 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.
Packaged: 2016-11-08 23:04:39 UTC; ashleypetersen

Description: 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.
Packaged: 2018-04-05 23:43:16 UTC; ashleypetersen

Description: 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
Imports: tibble, dplyr, purrr, tidyr, ggplot2, ggforce, paletteer,
Suggests: deldir, rmarkdown, testthat (>= 3.0.0)

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

Title: Functional Latent Data Models for Clustering Heterogeneous
Authors@R: c(person("Faicel", "Chamroukhi", role = c("aut"),
person("Florian", "Lecocq", role = c("aut", "trl", "cre"),
person("Marius", "Bartcus", role = c("aut","trl"),
Description: 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
The references are mainly the following ones.
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>.
Chamroukhi F., Glotin H. and Same A. (2013) <doi:10.1016/j.neucom.2012.10.030>.
Chamroukhi F. and Nguyen H-D. (2019) <doi:10.1002/widm.1298>.
Collate: flamingos-package.R RcppExports.R utils.R kmeans.R
Author: Faicel Chamroukhi [aut] (<https://orcid.org/0000-0002-5894-3103>),
Florian Lecocq [aut, trl, cre] (R port),