R packages for PK/PD modeling, BE/BA, drug stability, ivivc, etc.
These R packages are developed for data analysis of PK/PD modeling, bioequivalence/bioavailability (BE/BA), drug stability, in-vitro and in-vivo correlation (ivivc), as well as therapeutic drug monitoring (TDM). They include bear, ivivc, PKfit, stab and tdm.
R package for modelling anthropogenic deforestation
phcfM is an R package for modelling anthropogenic deforestation. It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time.
Event studies in several statistical packages
Software to perform event studies in several statistical packages, such as SAS, Stata and R.
User Friendly Data Analysis Tool for Interaction Data
TOPS provides the benchtop scientist with a free toolset to analyze, filter and visualize data from functional genomic gene-gene and gene-drug interaction screens with a flexible interface to accommodate various different technologies and analysis algorithms in addition to those already provided here.
R package for hierarchical species distribution models
hSDM is an R package for hierarchical species distribution models. Such models allows interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.
Tools to analyse and use passport data for biological collections.