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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "CGMissingDataR" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'CGMissingDataR: Impute Missing Glucose Values in CGM Data'
version: 0.0.2
doi: 10.32614/CRAN.package.CGMissingDataR
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 (MICE; Azur et al. (2011)
  <https://doi.org/10.1002/mpr.329>), Random Forest regression (Breiman (2001) <https://doi.org/10.1023/A:1010933404324>),
  k-nearest-neighbor regression (Zhang (2016) <https://doi.org/10.21037/atm.2016.03.37>),
  XGBoost (Chen and Guestrin (2016) <https://doi.org/10.1145/2939672.2939785>), LightGBM
  (Ke et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>),
  and ARIMA forecasting with the forecast framework (Hyndman and Khandakar (2008)
  <https://doi.org/10.18637/jss.v027.i03>). A Python-compatible backend uses 'reticulate'
  to call 'pandas', 'scikit-learn', 'statsmodels', Python 'xgboost', and optional
  Python '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/CGMmissingDataR
commit: b755964671a05e43cd1ee15630fe4a46a77b30fe
url: https://zhanglabuky.github.io/CGMmissingDataR/
date-released: '2026-05-29'
contact:
- family-names: Saraswat
  given-names: Shubh
  email: shubh.saraswat00@gmail.com
  orcid: https://orcid.org/0009-0009-2359-1484