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To enable quantitative trait loci mapping of neighbor effects, this package extends a single-marker regression to interval mapping. The theoretical background of the method is described in Sato et al. (2021) <doi:10.1093/g3journal/jkab017>.
This package provides functions to manipulate rational functions, including basic arithmetic operators, derivatives, and integrals with EXPLICIT forms.
Administrative regions and other spatial objects of the Czech Republic.
The receiver operating characteristic (ROC) curve is one of the most widely used tools for evaluating diagnostic and prognostic biomarkers across diverse scientific fields, particularly in medicine. Despite its ubiquity, ROC estimation and testing methods differ substantially in their assumptions and resulting curve properties. This package provides a unified framework for constructing, visualizing, and comparing parametric, nonparametric, semiparametric, and Bayesian ROC curves. ROCModels helps researchers identify and implement ROC inference methods most suitable for their data. See the accompanying vignette ROCModels_Package_Doc for a detailed introduction. Alonzo, T. A., and Pepe, M. S. (2002) <doi: 10.1093/biostatistics/3.3.421>, Andrews, D. F., and Herzberg, A. M. (1985) <doi: 10.1007/978-1-4612-5098-2>, Bamber, D. (1975) <doi: 10.1016/0022-2496(75)90001-2>, Cox, D. R. (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x>, Cox, D. R. (1975) <doi: 10.1093/biomet/62.2.269>, DeLong, E. R., DeLong, D. M., and Clarke-Pearson, D. L. (1988) <doi: 10.2307/2531595>, Dorfman, D. D., and Alf, E. (1969) <doi: 10.1016/0022-2496(69)90019-4>, Dorfman, D. D., Berbaum, K. S., and Metz, C. E. (1997) <doi: 10.1016/s1076-6332(97)80013-x>, Erkanli, A., Sung, L., and Stamey, J. D. (2006) <doi: 10.1002/sim.2496>, Faraggi, D., and Reiser, B. (2002) <doi: 10.1002/sim.1228>, Ghebremichael, M., and Habtemicael, S. (2018) <doi: 10.1080/02664763.2017.1420758>, Ghebremichael, M., and Michael, H. (2024) <doi: 10.1080/03610918.2022.2032159>, Ghebremichael, M., Michael, H., Tubbs, J., and Paintsil, E. (2019) <doi: 10.3844/jmssp.2019.55.64>, Gönen, M., and Heller, G. (2010) <doi: 10.1177/0272989X09360067>, Gopalakrishnan, V., Bose, E., Nair, U., Cheng, Y., and Ghebremichael, M. (2020) <doi: 10.1186/s12879-020-05458-w>, Green, D. M., and Swets, J. A. (1966, ISBN:0471324205), Gu, J., and Ghosal, S. (2009) <doi: 10.1016/j.jspi.2008.09.014>, Gu, Y., Ghosal, S., and Roy, A. (2008) <doi: 10.1002/sim.3366>, Guidoum, A. C. (2020) <doi: 10.32614/CRAN.package.kedd>, <doi: 10.48550/arXiv.2012.06102>, Guo, B. (2015) <https://d-scholarship.pitt.edu/23590/1/Guo_Ben_thesis_12-2014.pdf>, Hanley, J. A., and McNeil, B. J. (1982) <doi: 10.1148/radiology.143.1.7063747>, Hsieh, F., and Turnbull, B. W. (1996) <doi: 10.1214/aos/1033066197>, Hussain, E. (2012) <doi: 10.6000/1927-5129.2012.08.02.09>, Ishwaran, H., and James, L. F. (2002) <doi: 10.1198/106186002411>, Jokiel-Rokita, A., and Topolnicki, R. (2020) <doi: 10.1016/j.csda.2019.106820>, Krzanowski, W. J., and Hand, D. J. (2009) <doi: 10.1201/9781439800225>, Kundu, D., and Gupta, R. D. (2006) <doi: 10.1109/TR.2006.874918>, Lloyd, C. J. (1998) <doi: 10.1080/01621459.1998.10473797>, Lehmann, E. L. (1953) <doi: 10.1214/aoms/1177729080>, Metz, C. E., Herman, B. A., and Shen, J. H. (1998) <doi:10.1002/(SICI)1097-0258(19980515)17:9%3C1033::AID-SIM784%3E3.0.CO;2-Z>, Pepe, M. S. (2003) <doi: 10.1093/oso/9780198509844.001.0001>, Pundir, S., and Amala, R. (2014) <doi: 10.22237/jmasm/1398917940>, Silverman, B. W. (2018) <doi: 10.1201/9781315140919>, Yeo, I. K., and Johnson, R. A. (2000) <doi: 10.1093/biomet/87.4.954>, Zhou, X. H., McClish, D. K., and Obuchowski, N. A. (2009) <doi: 10.1002/9780470906514>, Zou, K. H., Hall, W. J., and Shapiro, D. E. (1997) <doi: 10.1002/(SICI)1097-0258(19971015)16:19%3C2143::AID-SIM655%3E3.0.CO;2-3>.
Electrical properties of resistor networks using matrix methods.
OpenRefine (formerly Google Refine') is a popular, open source data cleaning software. This package enables users to programmatically trigger data transfer between R and OpenRefine'. Available functionality includes project import, export and deletion.
This package provides a single key function, Require that makes rerun-tolerant versions of install.packages and require for CRAN packages, packages no longer on CRAN (i.e., archived), specific versions of packages, and GitHub packages. This approach is developed to create reproducible workflows that are flexible and fast enough to use while in development stages, while able to build snapshots once a stable package collection is found. As with other functions in a reproducible workflow, this package emphasizes functions that return the same result whether it is the first or subsequent times running the function, with subsequent times being sufficiently fast that they can be run every time without undue waiting burden on the user or developer.
Automatically apply different strategies to optimize R code. rco functions take R code as input, and returns R code as output.
This package provides a classifier independent filter method for high-dimensional gene-expression feature selection. The Run Purity Weighted Nearest Shrunken Centroid ('RPWNSC') score ranks genes by multiplying a run based purity score, which measures the compactness of class labels after sorting samples by each feature, by a scaled nearest shrunken centroid score, which measures standardized class centroid separation relative to within class variation. The top ranked features can then be used with downstream classifiers without wrapper search, feature clustering, or classifier dependent training. Amjad Ali, Zardad Khan, Saeed Aldahmani (2026) <doi:10.1016/j.mlwa.2026.100947>.
Package runonce helps automating the saving of long-running code to help running the same code multiple times. If you run some long-running code once, it saves the result in a file on disk. Then, if the result already exists, i.e. if the code has already been run and its output has already been saved, it just reads the result from the stored file instead of running the code again.
Conduct simulations of the Response Adaptive Block Randomization (RABR) design to evaluate its type I error rate, power and operating characteristics for binary and continuous endpoints. For more details of the proposed method, please refer to Zhan et al. (2021) <doi:10.1002/sim.9104>.
Implementation of the RPC-JSON API for Bitcoin and utility functions for address creation and content analysis of the blockchain.
Placental epigenetic clock to estimate aging based on gestational age using DNA methylation levels, so called placental epigenetic clock (PlEC). We developed a PlEC for the 2024 Placental Clock DREAM Challenge (<https://www.synapse.org/Synapse:syn59520082/wiki/628063>). Our PlEC achieved the top performance based on an independent test set. PlEC can be used to identify accelerated/decelerated aging of placenta for understanding placental dysfunction-related conditions, e.g., great obstetrical syndromes including preeclampsia, fetal growth restriction, preterm labor, preterm premature rupture of the membranes, late spontaneous abortion, and placental abruption. Detailed methodologies and examples are documented in our vignette, available at <https://herdiantrisufriyana.github.io/rplec/doc/placental_aging_analysis.html>.
Facilitates making a connection to the Revenera API and executing various queries. You can use it to get event data and metadata. The Revenera documentation is available at <https://rui-api.redoc.ly/>. This package is not supported by Flexera (owner of the software).
This package implements safe policy learning under regression discontinuity designs with multiple cutoffs, based on Zhang et al. (2022) <doi:10.48550/arXiv.2208.13323>. The learned cutoffs are guaranteed to perform no worse than the existing cutoffs in terms of overall outcomes. The rdlearn package also includes features for visualizing the learned cutoffs relative to the baseline and conducting sensitivity analyses.
The minimum covariance determinant estimator is used to perform robust quadratic discriminant analysis, including cross-validation. References: Friedman J., Hastie T. and Tibshirani R. (2009). "The elements of statistical learning", 2nd edition. Springer, Berlin. <doi:10.1007/978-0-387-84858-7>.
Interface to JDemetra+ 3.x (<https://github.com/jdemetra>) time series analysis software. It provides a variety of methods for temporal disaggregation & interpolation, benchmarking, reconciliation and calendarization. It incorporates statistical methods described in the latest European Statistical System (ESS) guidelines on temporal disaggregation, benchmarking, and reconciliation (2018 edition). The package implements highly efficient algorithms for fast and reliable computation.
This package provides access to the Ravelry API <https://www.ravelry.com/groups/ravelry-api>. An R wrapper for pulling data from Ravelry.com', an organizational tool for crocheters, knitters, spinners, and weavers. You can retrieve pattern, yarn, author, and shop information by search or by a given id.
Simple methods to generate attractive random colors. The random colors are from a wrapper of randomColor.js <https://github.com/davidmerfield/randomColor>. In addition, it also generates optimally distinct colors based on k-means (inspired by IWantHue <https://github.com/medialab/iwanthue>).
Variable importance rankings depend on the method, the random seed and the resample used to compute them. This package treats every source of importance as a judge expressing a ranking over the predictors, and synthesises those rankings into a Kemeny median ranking with ties. Uncertainty about the consensus is quantified through bootstrap rank confidence sets, top-k probabilities and clustering of disagreeing judges.
Robust methods for estimating the parameters of multivariate Gaussian linear models.
Client for ChromaDB', a vector database for storing and querying embeddings. This package provides a convenient interface to interact with the REST API of ChromaDB <https://docs.trychroma.com>.
This package uses either the statconnDCOM server (via the rcom package) or the RDCOMClient to communicate with MS-Word via the COM interface.
High resolution vector country boundaries derived from Natural Earth data, can be plotted in rworldmap.