Package: smriti 0.2.0

Xiyuan Guo

smriti: Automated Routing Engine for Longitudinal Missing Data

Provides an automated routing engine for longitudinal missing data. It utilizes a Lagrange-constrained Random Forest based on sample size, missingness rate, and skew to preserve structural variance.

Authors:Xiyuan Guo [aut, cre]

smriti_0.2.0.tar.gz
smriti_0.2.0.tar.gz(r-4.7-arm64)smriti_0.2.0.tar.gz(r-4.7-x86_64)smriti_0.2.0.tar.gz(r-4.6-arm64)smriti_0.2.0.tar.gz(r-4.6-x86_64)
smriti_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
smriti/json (API)

# Install 'smriti' in R:
install.packages('smriti', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

3.30 score 215 downloads 6 exports 2 dependencies

Last updated from:ed473ff47f. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK130
linux-devel-x86_64OK138
source / vignettesOK229
linux-release-arm64OK133
linux-release-x86_64OK136
wasm-releaseOK126

Exports:smriti_fimlsmriti_forestsmriti_imputesmriti_mismriti_micesmriti_ranger

Dependencies:RcppRcppArmadillo

Introduction to smriti: Structural Variance Preservation

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Jun 06 2026.

Last update: 2026-06-05
Started: 2026-05-21

Outlier-Robust Longitudinal Imputation with smriti

Rendered fromoutlier-robust.Rmdusingknitr::rmarkdownon Jun 06 2026.

Last update: 2026-06-05
Started: 2026-06-05