# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ 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 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) ), Random Forest regression using 'ranger' (Breiman (2001) ), k-nearest-neighbor regression using 'FNN' (Zhang (2016) ), 'XGBoost' using 'xgboost' (Chen and Guestrin (2016) ), 'LightGBM' using 'lightgbm' (Ke et al. (2017) ), and ARIMA forecasting using 'forecast' (Hyndman and Khandakar (2008) ). 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://cran.r-universe.dev repository-code: https://github.com/ZhangLabUKY/imputeCGMR commit: f435739579210efd7ec052ab1a8870fc064fcdbd url: https://zhanglabuky.github.io/imputeCGMR/ date-released: '2026-07-16' contact: - family-names: Saraswat given-names: Shubh email: shubh.saraswat00@gmail.com orcid: https://orcid.org/0009-0009-2359-1484