Use leaf physiognomic methods to reconstruct mean annual
    temperature (MAT), mean annual precipitation (MAP), and leaf dry mass
    per area (Ma), along with other useful quantitative leaf traits. Methods
    in this package described in Lowe et al. (in review).

A robust identification of differential binding sites method for analyzing ChIP-seq (Chromatin Immunoprecipitation Sequencing) 
    comparing two samples that considers an ensemble of finite mixture models combined with a local false discovery rate (fdr) 
    allowing for flexible modeling of data. Methods for Differential Identification using Mixture Ensemble (DIME) is described in: 
    Taslim et al., (2011) <doi:10.1093/bioinformatics/btr165>.

Simple Principal Components Analysis (PCA) and (Multiple)
    Correspondence Analysis (CA) based on the Singular Value Decomposition
    (SVD). This package provides S4 classes and methods to compute,
    extract, summarize and visualize results of multivariate data
    analysis. It also includes methods for partial bootstrap validation
    described in Greenacre (1984, ISBN: 978-0-12-299050-2) and Lebart et
    al. (2006, ISBN: 978-2-10-049616-7).

A set of tools to extract bibliographic content from 'Digital Science Dimensions' using 'DSL' API <https://www.dimensions.ai/dimensions-apis/>.

The 'DImodels' package is suitable for analysing data from biodiversity and ecosystem function studies using the Diversity-Interactions (DI) modelling approach introduced by Kirwan et al. (2009) <doi:10.1890/08-1684.1>. Suitable data will contain proportions for each species and a community-level response variable, and may also include additional factors, such as blocks or treatments. The package can perform data manipulation tasks, such as computing pairwise interactions (the DI_data() function), can perform an automated model selection process (the autoDI() function) and has the flexibility to fit a wide range of user-defined DI models (the DI() function).

An add-on package to 'DImodels' for the fitting of biodiversity and ecosystem function relationship study data with multiple ecosystem function responses and/or time points. This package uses the multivariate and repeated measures Diversity-Interactions (DI) methods developed by Kirwan et al. (2009) <doi:10.1890/08-1684.1>, Finn et al. (2013) <doi:10.1111/1365-2664.12041>, and Dooley et al. (2015) <doi:10.1111/ele.12504>.