Secant acceleration applied to derivative-free Spectral
  Residual Methods for solving large-scale nonlinear systems of
  equations. The main reference follows: E. G. Birgin and
  J. M. Martinez (2022) <doi:10.1137/20M1388024>.

Decomposing value added growth into explanatory factors.
    A cost constrained value added function is defined to specify the 
    production frontier. Industry estimates can also be aggregated using 
    a weighted average approach.
    Details about the methodology and data can be found in Diewert and Fox (2018)
    <doi:10.1093/oxfordhb/9780190226718.013.19>
    and Zeng, Parsons, Diewert and Fox (2018)
    <https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/emg2018-6_SZeng_EMG-Slides.pdf>.

Performs Bayesian model averaging for capture-recapture. This includes code to stratify records, check the strata for suitable overlap to be used for capture-recapture, and some functions to plot the estimated population size.

Feature selection from high dimensional data using a diploid
    genetic algorithm with Incomplete Dominance for genotype to phenotype mapping
    and Random Assortment of chromosomes approach to recombination.

Analyses gene expression data derived from experiments to detect differentially expressed genes by employing the concept of majority voting with five different statistical models. It includes functions for differential expression analysis, significance testing, etc. It simplifies the process of uncovering meaningful patterns and trends within gene expression data, aiding researchers in downstream analysis. Boyer, R.S., Moore, J.S. (1991) <doi:10.1007/978-94-011-3488-0_5>.

Provides a flexible container to manage and annotate Differential Gene 
    Expression (DGE) analysis results (Smythe et. al (2015) <doi:10.1093/nar/gkv007>).  
    The DGEobj has data slots for row (gene), col (samples), assays (matrix n-rows 
    by m-samples dimensions) and metadata (not keyed to row, col, or assays).  
    A set of accessory functions to deposit, query and retrieve subsets of a data 
    workflow has been provided.  Attributes are used to capture metadata such as 
    species and gene model, including reproducibility information such that a 3rd 
    party can access a DGEobj history to see how each data object was created or 
    modified.  Since the DGEobj is customizable and extensible it is not limited 
    to RNA-seq analysis types of workflows -- it can accommodate nearly any data 
    analysis workflow that starts from a matrix of assays (rows) by samples (columns).