Contains functions intended to facilitate the production of plant taxonomic monographs. The package includes functions to convert tables into taxonomic descriptions, lists of collectors and examined specimens. Additionally, wrapper functions to batch the production of phenology charts and distributional and diversity maps are also available.

Contains functions intended to facilitate the production of plant taxonomic monographs. The package includes functions to convert tables into taxonomic descriptions, lists of collectors, examined specimens, and can generate a monograph skeleton. Additionally, wrapper functions to batch the production of phenology charts and distributional and diversity maps are also available.

Estimation for multivariate normal data with monotone missingness
Estimation of multivariate normal data of arbitrary dimension
where the pattern of missing data is monotone. Through the use of
partial least squares and principal component regressions,
where standard regressions fail,
the package can handle an (almost) arbitrary amount of missing
data.  The current version supports maximum likelihood inference.
Future versions will provide a means of sampling from a Bayesian
posterior.

Estimation of multivariate normal data of arbitrary dimension
where the pattern of missing data is monotone. Through the use of
parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.),
where standard regressions fail, the package can handle an (almost)
arbitrary amount of missing data.  The current version supports
maximum likelihood inference.  Future versions will provide a means
of sampling from a Bayesian posterior.

Estimation of multivariate normal data of arbitrary dimension
where the pattern of missing data is monotone. Through the use of
parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.),
where standard regressions fail, the package can handle an
(almost) arbitrary amount of missing data.  The current version
supports maximum likelihood inference and an alpha implementation
of a Bayesian version employing a Bayesian lasso.  A fully
functional standalone (alpha) interface to the Bayesian lasso
(from Park & Casella) is also provided