Calculates cost surfaces based on slope to be used when modelling pathways and movement potential within a landscape (Lewis, 2021) <doi:10.1007/s10816-021-09522-w>.

Utilities for querying plain text accounting files from 'Ledger', 'HLedger', and 'Beancount'.

Educational tool for teaching of statistics 
    and mathematics in primary and higher education. The objective is 
    to assist in teaching/learning for both student study planning 
    and teacher teaching strategies. The 'leem' package will try to bring, 
    in a simple and at the same time in-depth, 
    knowledge of statistics and mathematics to everyone 
    who wants to study these areas of knowledge. The main function of the 
    package is 'leem()' function.

Complete analytical environment for the construction and analysis
             of matrix population models and integral projection models.
             Includes the ability to construct historical matrices, which are
             2d matrices comprising 3 consecutive times of demographic
             information. Estimates both raw and function-based forms of
             historical and standard ahistorical matrices. It also estimates
             function-based age-by-stage matrices and raw and function-based
             Leslie matrices.

Functions implementing multivariate state space models for purposes of time series analysis and forecasting.
             The focus of the package is on multivariate models, such as Vector Exponential Smoothing,
             Vector ETS (Error-Trend-Seasonal model) etc. It currently includes Vector Exponential
             Smoothing (VES, de Silva et al., 2010, <doi:10.1177/1471082X0901000401>), Vector ETS and
             simulation function for VES.

Facilitates access to the Comparative Legislators Database (CLD). The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 67,000 contemporary and historical politicians from 16 countries.

Constructs genotype x environment interaction (GxE) models where
    G is a weighted sum of genetic variants (genetic score) and E is a weighted
    sum of environments (environmental score) using the alternating optimization algorithm 
    by Jolicoeur-Martineau et al. (2017) <arXiv:1703.08111>. This approach has greatly 
    enhanced predictive power over traditional GxE models which include only a single 
    genetic variant and a single environmental exposure. Although this approach was 
    originally made for GxE modelling, it is flexible and does not require the use of 
    genetic and environmental variables. It can also handle more than 2 latent variables 
    (rather than just G and E) and 3-way interactions or more. The LEGIT model produces 
    highly interpretable results and is very parameter-efficient thus it can even be 
    used with small sample sizes (n < 250). Tools to determine the type of interaction
    (vantage sensitivity, diathesis-stress or differential susceptibility), with any 
    number of genetic variants or environments, are available <arXiv:1712.04058>. The 
    software can now produce mixed-effects LEGIT models through the lme4 package.