Enables binary package installations on Linux distributions.
    Provides functions to manage packages via the distribution's package
    manager. Also provides transparent integration with R's install.packages()
    and a fallback mechanism. When installed as a system package, interacts
    with the system's package manager without requiring administrative
    privileges via an integrated D-Bus service; otherwise, uses sudo.
    Currently, the following backends are supported: DNF, APT, ALPM.

Fit Bayesian models with a focus on the spatial econometric models.

Efficient simulation of Brownian semistationary (BSS) processes using the hybrid simulation scheme, as described in 
    Bennedsen, Lunde, Pakkannen (2017) <arXiv:1507.03004v4>, as well as functions to fit BSS processes
    to data, and functions to estimate the stochastic volatility process of a BSS process.

Functions to compute the asymptotic covariance matrices of mixing and unmixing matrix estimates of the following blind source separation (BSS) methods: symmetric and squared symmetric FastICA, regular and adaptive deflation-based FastICA, FOBI, JADE, AMUSE and deflation-based and symmetric SOBI. Also functions to estimate these covariances based on data are available.

Computation of the minimum sample size using the Average
    Coverage Criterion or the Average Length Criterion for estimating
    binomial proportions using beta prior distributions. For more details
    see Costa (2025) <DOI:10.1007/978-3-031-72215-8_14>.

Efficient methods for Bayesian inference of state space models 
    via Markov chain Monte Carlo (MCMC) based on parallel 
    importance sampling type weighted estimators 
    (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>), 
    particle MCMC, and its delayed acceptance version. 
    Gaussian, Poisson, binomial, negative binomial, and Gamma
    observation densities and basic stochastic volatility models 
    with linear-Gaussian state dynamics, as well as general non-linear Gaussian 
    models and discretised diffusion models are supported. 
    See Helske and Vihola (2021, <doi:10.32614/RJ-2021-103>) for details.