Author: Olivier Bouriaud, Ernst van der Maaten, Marieke van der Maaten-Theunissen and Marko Smiljanic
Maintainer: Ernst van der Maaten <ernst.vandermaaten@gmail.com>
Description: Various functions to import, verify, process and plot high-resolution dendrometer using daily and stem-cycle approaches.
Depends: R (>= 3.2.0), forecast, graphics, grDevices, pspline, stats,

Title: Forest Estimations and Dendrometric Computations
Authors@R: c(person(given = "Narcisse", family = "Yehouenou",
role = c("aut", "cre"), email = "narcisstar211@gmail.com"),
person("Information and Communication Technology for you ONG (ICT4U-ONG)",
Description: Computation of dendrometric and structural
parameters from forest inventory data. The objective is to provide an
user-friendly R package for researchers, ecologists, foresters,
statisticians, loggers and others persons who deal with forest inventory
data. Useful conversion of angle value from degree to radian, conversion from
angle to slope (in percentage) and their reciprocals as well as principal
angle determination are also included. Position and dispersion parameters
usually found in forest studies are implemented. The package contains
Fibonacci series, its extensions and the Golden Number computation.
Useful references are Arcadius Y. J. Akossou, Soufianou Arzouma,
Eloi Y. Attakpa, Noël H. Fonton and Kouami Kokou (2013) <doi:10.3390/d5010099>
and W. Bonou, R. Glele Kakaï, A.E. Assogbadjo, H.N. Fonton, B. Sinsin (2009)
Information and Communication Technology for you ONG (ICT4U-ONG) [fnd]

Title: Sorting and reordering dendrogram nodes.
Description: This package includes functions to optimize ordering of nodes in a dendrogram,
without affecting the meaning of the dengrogram. A dengrogram can be sorted based
on the average distance of subtrees, or based on the smallest distance value.
These sorting methods improve readability and interpretability of tree structure,
especially for tasks such as comparison of different disntance measures or linkage
types and identification of tight clusters and outliers. As a result, it also
introduces more meaningful reordering for a coupled heatmap visualization.