Package: hdiVAR
Type: Package
Title: Statistical Inference for Noisy Vector Autoregression
Version: 1.0.2
Authors@R: c(person("Xiang", "Lyu", role = c("aut","cre"), email="xianglyu.public@gmail.com"),
             person("Jian", "Kang", role = c("aut")),
             person("Lexin", "Li", role = c("aut")))
Description: The model is high-dimensional vector autoregression with
        measurement error, also known as linear gaussian state-space
        model. Provable sparse expectation-maximization algorithm is
        provided for the estimation of transition matrix and noise
        variances. Global and simultaneous testings are implemented for
        transition matrix with false discovery rate control. For more
        information, see the accompanying paper: Lyu, X., Kang, J., &
        Li, L. (2023). "Statistical inference for high-dimensional
        vector autoregression with measurement error", Statistica
        Sinica.
Imports: lpSolve, abind
License: GPL (>= 2)
Depends: R (>= 3.1)
Encoding: UTF-8
RoxygenNote: 7.2.3
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Author: Xiang Lyu [aut, cre], Jian Kang [aut], Lexin Li [aut]
Maintainer: Xiang Lyu <xianglyu.public@gmail.com>
NeedsCompilation: no
Packaged: 2026-06-14 06:31:37 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2023-05-14 21:00:02 UTC
RemoteUrl: https://github.com/cran/hdiVAR
RemoteRef: HEAD
RemoteSha: b10b8997ca53791d9e53f13892eaa1bb78084ef7