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ngme2
View on CRAN: Click
here
Download and install ngme2 package within the R console
Install from CRAN:
install.packages("ngme2")
Install from Github:
library("remotes")
install_github("cran/ngme2") Install by package version:
library("remotes")
install_version("ngme2", "0.9.7") Attach the package and use:
library("ngme2")
Maintained by
Xiaotian Jin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-28
Latest Update: 2026-04-28
Description:
Fits and analyzes linear latent non-Gaussian models for temporal, spatial, and space-time data. The package provides model components for autoregressive and Ornstein-Uhlenbeck processes, random walks, Matern fields based on stochastic partial differential equations, separable and non-separable space-time models, graph-based Matern models, bivariate type-G fields, and user-defined sparse operators. Latent fields and observation models can use Gaussian and non-Gaussian noise distributions, including normal inverse Gaussian, generalized asymmetric Laplace, and skew-t distributions. Functions are included for simulation, likelihood-based estimation, prediction, cross-validation, convergence diagnostics, stochastic gradient optimization, batch-means confidence intervals, and posterior-like sampling. The modeling framework is described in Bolin, Jin, Simas and Wallin (2026) "A Unified and Computationally Efficient Non-Gaussian Statistical Modeling Framework" <doi:10.48550/arXiv.2602.23987>.
How to cite:
Xiaotian Jin (2026). ngme2: Linear Latent Non-Gaussian Models with Flexible Distributions. R package version 0.9.7, https://cran.r-project.org/web/packages/ngme2. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-07-09 06:24), 0.9.7 (2026-04-28 20:50)
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