c(person("J.W.M.", "Pullens", email = "jeroenpullens@gmail.com", role =
c("aut", "cre")),
person("R.", "Silveyra Gonzalez",role="aut"),
person("M.","Bagnara",role ="aut"),
person("F.","Hartig",role="aut"))
Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The test data can be downloaded from http://jeroenpullens.github.io/NUCOMBog_data/. And the executable of the model can downloaded from https://github.com/jeroenpullens/source_NUCOMBog-executable.
J.W.M. Pullens [aut, cre],
R. Silveyra Gonzalez [aut],
M. Bagnara [aut],
F. Hartig [aut]

Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The test data can be downloaded from http://jeroenpullens.github.io/NUCOMBog_data/. And the executable of the model can downloaded from https://github.com/jeroenpullens/source_modelMEE.

Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The executable of the model can downloaded from <https://github.com/jeroenpullens/source_modelMEE>.

Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The executable of the model can downloaded from <https://github.com/jeroenpullens/NUCOMBog>.

Nonparametric Varying Coefficient Spike-and-Slab Lasso
EM algorithm for fitting Bayesian varying coefficient models with the nonparametric varying coefficient spike-and-slab lasso of Bai et al. (2020) <arXiv:1907.06477>. Also fits penalized frequentist varying coefficient models with the group lasso, group smoothly clipped absolute deviation, and group minimax concave penalty.

Using Needleman-Wunsch to Match Sample Names
The Needleman-Wunsch global alignment algorithm can be
used to find approximate matches between sample names in different
data sets. See Wang et al. (2010) <doi:10.4137/CIN.S5613>.