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authorGlenn Johnson <glenn-johnson@uiowa.edu>2021-01-17 14:07:40 -0600
committerGitHub <noreply@github.com>2021-01-17 14:07:40 -0600
commit41ca013069ba2787cf821b1aa0c67481510cf3c2 (patch)
treea380372073e8eb62b7e2655ee6103f82cc829b38
parenta54e4322e51523452fc566a13418b2d8709e0740 (diff)
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add version 1.6.8.1 to r-lava (#21069)
-rw-r--r--var/spack/repos/builtin/packages/r-lava/package.py13
1 files changed, 12 insertions, 1 deletions
diff --git a/var/spack/repos/builtin/packages/r-lava/package.py b/var/spack/repos/builtin/packages/r-lava/package.py
index a099ada943..81d87cb156 100644
--- a/var/spack/repos/builtin/packages/r-lava/package.py
+++ b/var/spack/repos/builtin/packages/r-lava/package.py
@@ -7,12 +7,23 @@ from spack import *
class RLava(RPackage):
- """Estimation and simulation of latent variable models."""
+ """Latent Variable Models
+
+ A general implementation of Structural Equation Models with latent
+ variables (MLE, 2SLS, and composite likelihood estimators) with both
+ continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen
+ (2013) <doi:10.1007/s00180-012-0344-y>). Mixture latent variable models and
+ non-linear latent variable models (Holst and Budtz-Joergensen (2019)
+ <doi:10.1093/biostatistics/kxy082>). The package also provides methods for
+ graph exploration (d-separation, back-door criterion), simulation of
+ general non-linear latent variable models, and estimation of influence
+ functions for a broad range of statistical models."""
homepage = "https://cloud.r-project.org/package=lava"
url = "https://cloud.r-project.org/src/contrib/lava_1.4.7.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/lava"
+ version('1.6.8.1', sha256='6d243fc86c67c78ff4763502d84ff2f0889c2e55d1a59afefb7a762887473ffa')
version('1.6.6', sha256='7abc84dd99cce450a45ac4f232812cde3a322e432da3472f43b057fb5c59ca59')
version('1.6.4', sha256='41c6eeb96eaef9e1bfb04b31f7203e250a5ea7e7860be4d95f7f96f2a8644718')
version('1.4.7', sha256='d5cbd4835a94855478efb93051eece965db116ead203f4dd4e09d9a12d52f4bf')