Persistent interface to 'Macaulay2' <http://www.math.uiuc.edu/Macaulay2/>
and front-end tools facilitating its use in the 'R' ecosystem. For details see
Kahle et. al. (2020) <doi:10.18637/jss.v093.i09>.

Provides binomial tree models for European, American and Asian
Options as well as Interest Rates. Monte Carlo Simulation and Methods for
Solving Differential Equations are also included.

Contains functions, which facilitate downloading, loading and preparing data from 'M5 Forecasting' challenges (by 'University of Nicosia', hosted on 'Kaggle').
The data itself is set of time series of different product sales in 'Walmart'.
The package also includes a ready-to-use built-in M5 subset named 'tiny_m5'.
For detailed information about the challenges, see:
Makridakis, S. & Spiliotis, E. & Assimakopoulos, V. (2020). <doi:10.1016/j.ijforecast.2021.10.009>.
ggplot2, knitr, testthat (>= 3.0.0), rmarkdown, zeallot

Package About Data Manipulation in Pure Base R
Data manipulation in one package and in base R.
Minimal. No dependencies.
'dplyr' and 'tidyr'-like in one place.
Nothing else than base R to build the package.

functions for multivariate AutoRegressive analysis
Estimation of multivariate AR models through a computationally-efficient stepwise least-squares algorithm (Neumaier and Schneider, 2001); the procedure is of particular interest for high-dimensional data without missing values such as geophysical fields.

Estimation of multivariate AR models through a
computationally-efficient stepwise least-squares
algorithm (Neumaier and Schneider, 2001); the
procedure is of particular interest for high-dimensional
data without missing values such as geophysical fields.

R functions for multivariate autoregressive analysis

R functions for the estimation and eigen-decomposition of multivariate autoregressive models.

Multivariate Bayesian Variable Selection Method Exploiting
Dependence among Outcomes
Kyu Ha Lee, Mahlet G. Tadesse, Brent A. Coull
Bayesian variable selection methods for data with continuous multivariate responses and multiple covariates.