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cff-version: 1.2.0
message: 'To cite package "imputeCGM" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'imputeCGM: Impute Missing Glucose Values in CGM Data'
version: 0.0.3
doi: 10.32614/CRAN.package.imputeCGM
abstract: Imputes missing glucose values in repeated-measures continuous glucose monitoring
  (CGM) data. Workflows create time-series features from raw timestamps, support model
  selection, and return the user's original columns plus an imputed glucose column.
  Methods include multiple imputation by chained equations using 'mice' (Azur et al.
  (2011) <https://doi.org/10.1002/mpr.329>), Random Forest regression using 'ranger'
  (Breiman (2001) <https://doi.org/10.1023/A:1010933404324>), k-nearest-neighbor regression
  using 'FNN' (Zhang (2016) <https://doi.org/10.21037/atm.2016.03.37>), 'XGBoost'
  using 'xgboost' (Chen and Guestrin (2016) <https://doi.org/10.1145/2939672.2939785>),
  'LightGBM' using 'lightgbm' (Ke et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>),
  and ARIMA forecasting using 'forecast' (Hyndman and Khandakar (2008) <https://doi.org/10.18637/jss.v027.i03>).
  A 'Python'-compatible backend uses 'reticulate' to call 'pandas', 'scikit-learn',
  'statsmodels', 'xgboost', and optional 'lightgbm'.
authors:
- family-names: Saraswat
  given-names: Shubh
  email: shubh.saraswat00@gmail.com
  orcid: https://orcid.org/0009-0009-2359-1484
- name: Hasin Shahed Shad
  email: hasin.shad@uky.edu
- family-names: Zhang
  given-names: Xiaohua Douglas
  email: douglas.zhang@uky.edu
  orcid: https://orcid.org/0000-0002-2486-7931
repository: https://zhanglabuky.r-universe.dev
repository-code: https://github.com/ZhangLabUKY/imputeCGMr
commit: 6617d693e56fdb4f8a7192753fc97e8cc97e1d6b
url: https://zhanglabuky.github.io/imputeCGMr/
date-released: '2026-07-17'
contact:
- family-names: Saraswat
  given-names: Shubh
  email: shubh.saraswat00@gmail.com
  orcid: https://orcid.org/0009-0009-2359-1484