Functions to estimate temporally regularized matrix factorizations (TRMF) for forecasting and imputing values in short but high-dimensional time series. Uses regularized alternating least squares to compute the factorization, allows for several types of constraints on matrix factors and natively handles weighted and missing data.

Evaluate inline or chunks of R code in template files and replace with their output modifying the resulting template.

These functions generate data frames on troop deployments and military basing using U.S. Department of Defense data on overseas military deployments. This package provides functions for pulling country-year troop deployment and basing data. Subsequent versions will hopefully include cross-national data on deploying countries.

It includes functions like tropical addition, tropical multiplication for vectors and matrices. In tropical algebra, the tropical sum of two numbers is their minimum and the tropical product of two numbers is their ordinary sum. For more information see also I. Simon (1988) Recognizable sets with multiplicities in the tropical semi ring: Volume 324 Lecture Notes I Computer Science, pages 107-120 <doi: 10.1007/BFb0017135>.

A compilation of fish stock assessment methods for the
    analysis of length-frequency data in the context of data-poor
    fisheries. Includes methods and examples included in the FAO
    Manual by P. Sparre and S.C. Venema (1998), "Introduction to tropical fish
    stock assessment" (<https://www.fao.org/documents/card/en/c/9bb12a06-2f05-5dcb-a6ca-2d6dd3080f65/>),
    as well as other more recent methods.

Class definitions and constructors for pseudo-vectors containing
    all permutations, combinations and subsets of objects taken from a vector.
    Simplifies working with structures commonly encountered in combinatorics.

The main function of the package aims to update 'lmer()'/'glmer()' models depending on their warnings, so trying to avoid convergence and singularity problems.

Provides methods for generating .dat files for use with the 'AMPL' 
    software using spatial data, particularly rasters. It includes support for 
    various spatial data formats and different problem types. By automating the 
    process of generating 'AMPL' datasets, this package can help streamline 
    optimization workflows and make it easier to solve complex optimization 
    problems. The methods implemented in this package are described in detail
    in a publication by Fourer et al. (<doi:10.1287/mnsc.36.5.519>).