Estimation tools for multidimensional Gaussian means using
    empirical Bayesian g-modeling. Methods are able to handle fully observed data as
    well as left-, right-, and interval-censored observations (Tobit
    likelihood); descriptions of these methods can be found in Barbehenn and
    Zhao (2023) <doi:10.48550/arXiv.2306.07239>. Additional, lower-level functionality based
    on Kiefer and Wolfowitz (1956) <doi:10.1214/aoms/1177728066> and Jiang and
    Zhang (2009) <doi:10.1214/08-AOS638> is provided that can be used to
    accelerate many empirical Bayes and nonparametric maximum likelihood
    problems.

The concept of Essential Biodiversity Variables (EBV, <https://geobon.org/ebvs/what-are-ebvs/>) 
    comes with a data structure based on the Network Common Data Form (netCDF). 
    The 'ebvcube' 'R' package provides functionality to easily create, access and 
    visualise this data. The EBV netCDFs can be downloaded from the EBV Data 
    Portal: Christian Langer/ iDiv (2020) <https://portal.geobon.org/>.

An implementation for estimating Effective control to 50% of growth
    inhibition (EC50) for multi isolates and stratified datasets. It implements 
    functions from the drc package in a way that is displayed a tidy data.frame 
    as output. Info about the drc package is available in Ritz C, Baty F, Streibig JC,
    Gerhard D (2015) <doi:10.1371/journal.pone.0146021>.

Support ecological analyses such as ordination and clustering. 
    Contains consistent and easy wrapper functions of 'stat', 'vegan', and 
    'labdsv' packages, and visualisation functions of ordination and clustering.

Fits Leroux model in spectral domain to estimate causal spatial effect as detailed in 
             Guan, Y; Page, G.L.; Reich, B.J.; Ventrucci, M.; Yang, S; (2020) <arXiv:2012.11767>.  
             Both the parametric and semi-parametric models are available.  The semi-parametric model 
             relies on 'INLA'.  The 'INLA' package can be obtained from <https://www.r-inla.org/>.