https://mtkurbucz-ucl.r-universe.devRecent package updates in mtkurbucz-uclR-universehttps://github.com/mtkurbucz-ucl.pnghttps://mtkurbucz-ucl.r-universe.devThu, 11 Dec 2025 23:40:02 GMTm.kurbucz@ucl.ac.uk (Marcell T. Kurbucz)Simplifies the creation, management, and updating of local databases using data extracted from 'Google Earth Engine' ('GEE'). It integrates with 'GEE' to store, aggregate, and process spatio-temporal data, leveraging 'SQLite' for efficient, serverless storage. The 'geeLite' package provides utilities for data transformation and supports real-time monitoring and analysis of geospatial features, making it suitable for researchers and practitioners in geospatial science. For details, see Kurbucz and Andrée (2025) "Building and Managing Local Databases from Google Earth Engine with the geeLite R Package" <https://hdl.handle.net/10986/43165>.https://github.com/r-universe/mtkurbucz-ucl/actions/runs/37761282188Thu, 11 Dec 2025 23:40:02 GMTgeeLite1.0.6successhttps://mtkurbucz-ucl.r-universe.devhttps://github.com/cran/geeLitegeeLite.RmdgeeLite.html'geeLite' R Package2025-07-21 09:51:252025-11-22 12:55:18m.kurbucz@ucl.ac.uk (Marcell T. Kurbucz)Implements 'SplitWise', a hybrid regression approach that transforms numeric variables into either single-split (0/1) dummy variables or retains them as continuous predictors. The transformation is followed by stepwise selection to identify the most relevant variables. The default 'iterative' mode adaptively explores partial synergies among variables to enhance model performance, while an alternative 'univariate' mode applies simpler transformations independently to each predictor. For details, see Kurbucz et al. (2025) <doi:10.48550/arXiv.2505.15423>.https://github.com/r-universe/mtkurbucz-ucl/actions/runs/38367770258Thu, 31 Jul 2025 05:46:58 GMTSplitWise1.0.2successhttps://mtkurbucz-ucl.r-universe.devhttps://github.com/cran/SplitWisesplitwise.Rmdsplitwise.htmlUsing the SplitWise Package with the mtcars Dataset2025-05-28 16:43:332025-07-31 05:46:58