Partitioned Local Depth for Community Structure in Data
Implementation of the Partitioned Local Depth (PaLD)
approach which provides a measure of local depth and the cohesion of a point
to another which  (together with a universal threshold for distinguishing
strong and weak ties) may be used to reveal local and global structure in
data, based on methods described in Berenhaut, Moore, and Melvin (2022)
<doi:10.1073/pnas.2003634119>. No extraneous inputs, distributional
assumptions, iterative procedures nor optimization criteria are employed.
This package includes functions for computing local depths and cohesion as
well as flexible functions for plotting community networks and displays of
cohesion against distance.

Alexander Correa-Metrio, Dunia Urrego, Kenneth Cabrera, Mark
Bush
basic statistical operations for paleoecology

Alexander Correa-Metrio, Dunia H. Urrego, Kenneth R. Cabrera,
Mark B. Bush
Transfer functions and statistical operations for
paleoecology

Modeling evolution in paleontological time-series
This package facilitates analysis of paleontological sequences of trait values from an evolving lineage.  Functions are provided to fit, using maximum likelihood, evolutionary models including random walk (biased and unbiased forms) and stasis models.

This package facilitates analysis of paleontological sequences of trait values from an evolving lineage.  Functions are provided to fit, using maximum likelihood, evolutionary models including unbiased random walks, directional evolution and stasis models.

This package facilitates analysis of paleontological sequences of trait values from an evolving lineage.  Functions are provided to fit, using maximum likelihood, evolutionary models including unbiased random walks, directional evolution, stasis, and Ornstein-Uhlenbeck models.  Newly added to this version (0.3-1) are functions to analyze punctuations and models in which evolutionary dynamics change over the course of a time-series of trait values.

This package facilitates analysis of paleontological
sequences of trait values from an evolving lineage.  Functions
are provided to fit, using maximum likelihood, evolutionary
models including unbiased random walks, directional evolution,
stasis, and Ornstein-Uhlenbeck models.  Newly added to this
version (0.3-1) are functions to analyze punctuations and
models in which evolutionary dynamics change over the course of
a time-series of trait values.