Provides functions to work with directed (asymmetric) and 
    undirected (symmetric) spatial networks. It makes the creation of 
    connectivity matrices easier, i.e. a binary matrix of dimension n x n, where 
    n is the number of nodes (sampling units) indicating the presence (1) or  
    the absence (0) of an edge (link) between pairs of nodes. Different network
    objects can be produced by 'chessboard': node list, neighbor list, edge 
    list, connectivity matrix. It can also produce objects that will be used 
    later in Moran's Eigenvector Maps (Dray et al. (2006) <doi:10.1016/j.ecolmodel.2006.02.015>)
    and Asymetric Eigenvector Maps (Blanchet et al. (2008) <doi:10.1016/j.ecolmodel.2008.04.001>), 
    methods available in the package 'adespatial' (Dray et al. (2023) 
    <https://CRAN.R-project.org/package=adespatial>). This work is part of the 
    FRB-CESAB working group Bridge 
    <https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/bridge/>.

Datasets of the International Chess Federation's player ratings and country information analysed in the book Antony Unwin (2024, ISBN:978-0367674007) "Getting (more out of) Graphics".

Applies the change-in-effect estimate method to assess confounding 
    effects in medical and epidemiological research (Greenland & Pearce (2016) 
    <doi:10.1146/annurev-publhealth-031914-122559> ). It starts with a crude model 
    including only the outcome and exposure variables. At each of the subsequent 
    steps, one variable which creates the largest change among the remaining variables 
    is selected. This process is repeated until all variables have been entered into 
    the model (Wang Z. Stata Journal 2007; 7, Number 2, pp. 183–196). Currently, the 'chest' 
    package has functions for linear regression, logistic regression, negative 
    binomial regression, Cox proportional hazards model and conditional logistic 
    regression.

Provides tools to process and analyze chest expansion using 3D marker data from motion capture systems. Includes functions for data processing, marker position adjustment, volume calculation using convex hulls, and visualization in 2D and 3D. Barber et al. (1996) <doi:10.1145/235815.235821>. TAMIYA Hiroyuki et al. (2021) <doi:10.1038/s41598-021-01033-8>.