methods, stats, graphics, reticulate (>= 1.8), ggplot2,
memoise

A package for modelling anthropogenic deforestation

phcfM is an R package for modelling anthropogenic
deforestation. It was initially developed to obtain REDD
baseline scenarios of deforestation for the "programme
holistique de conservation des forets a Madagascar" (from which
the package is named after). Parameter inference is done in a
hierarchical Bayesian framework. Markov chains Monte Carlo
(MCMC) are coded in C++ using the Scythe statistical library to
maximize computation efficiency.

phcfM is an R package for modelling anthropogenic
deforestation. It was initially developed to obtain REDD+
baseline scenarios of deforestation for the "programme
holistique de conservation des forets a Madagascar" (from which
the package is named after). Parameter inference is done in a
hierarchical Bayesian framework. Markov chains Monte Carlo
(MCMC) are coded in C++ using the Scythe statistical library to
maximize computation efficiency.

Permutation Testing in High-Dimensional Linear Models
Provides permutation methods for testing in high-dimensional linear models.
The tests are often robust against heteroscedasticity and non-normality
and usually perform well under anti-sparsity.
See Hemerik and Goeman (2018) <doi:10.1007/s11749-017-0571-1>.

Provides permutation methods for testing in high-dimensional linear models.
The tests are often robust against heteroscedasticity and non-normality
and usually perform well under anti-sparsity.
See Hemerik, Thoresen and Finos (2021) <doi:10.1080/00949655.2020.1836183>.

The package for drawing pretty heatmaps in R. The ordinary
heatmap function in R has several drawbacks, when it comes to
producing publication quality heatmaps. It is hard to produce
pictures with consistent text, cell and overall sizes and
shapes. The function pheatmap tries to alleviate the problems
by offering more fine grained control over heatmap dimensions
and appearance.

A package for drawing pretty heatmaps in R. The ordinary
heatmap function in R has several drawbacks when it comes to
producing publication quality heatmaps. It is hard to produce
pictures with consistent text, cell and overall sizes and
shapes. The function pheatmap tries to alleviate the problems
by offering more fine grained control over heatmap dimensions
and appearance.