Gene-based association tests using the actual impurity reduction (AIR) variable importance. The function aggregates AIR importance measures from a group of SNPs or probes and outputs a p-value for each gene. The procedures builds upon the method described in <doi:10.1093/Bioinformatics/Bty373> and will be published soon.

A replication of key functionality from 'dplyr' and the wider 'tidyverse' using only 'base'.

Population dynamic models underpin a range of analyses and applications in ecology and epidemiology. The various approaches for analysing population dynamics models (MPMs, IPMs, ODEs, POMPs, PVA) each require the model to be defined in a different way. This makes it difficult to combine different modelling approaches and data types to solve a given problem. 'pop' aims to provide a flexible and easy to use common interface for constructing population dynamic models and enabling to them to be fitted and analysed in lots of different ways.

Simulate the dynamic of lion populations using a specific Individual-Based Model (IBM) compiled in C.

Simulate the dynamic of wolf populations using a specific Individual-Based Model (IBM) compiled in C, see Chapron et al. (2016) <doi:10.1016/j.ecolmodel.2016.08.012>.

Infers the trends of one or several animal populations over time 
    from series of counts. It does so by accounting for count precision 
    (provided or inferred based on expert knowledge, e.g. guesstimates), 
    smoothing the population rate of increase over time, and accounting for the
    maximum demographic potential of species. Inference is carried out in a 
    Bayesian framework. This work is part of the FRB-CESAB working group
    AfroBioDrivers 
    <https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/afrobiodrivers/>.

Construct and analyze projection matrix models from a demography study of marked individuals classified by age or stage. The package covers methods described in Matrix Population Models by Caswell (2001) and Quantitative Conservation Biology by Morris and Doak (2002).