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r-st
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public |
Implements the "shrinkage t" statistic introduced in Opgen-Rhein and Strimmer (2007) <DOI:10.2202/1544-6115.1252> and a shrinkage estimate of the "correlation-adjusted t-score" (CAT score) described in Zuber and Strimmer (2009) <DOI:10.1093/bioinformatics/btp460>. It also offers a convenient interface to a number of other regularized t-statistics commonly employed in high-dimensional case-control studies.
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2025-04-22 |
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r-sqldf
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public |
The sqldf() function is typically passed a single argument which is an SQL select statement where the table names are ordinary R data frame names. sqldf() transparently sets up a database, imports the data frames into that database, performs the SQL select or other statement and returns the result using a heuristic to determine which class to assign to each column of the returned data frame. The sqldf() or read.csv.sql() functions can also be used to read filtered files into R even if the original files are larger than R itself can handle. 'RSQLite', 'RH2', 'RMySQL' and 'RPostgreSQL' backends are supported.
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2025-04-22 |
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r-spthin
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public |
A set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling.
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2025-04-22 |
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r-spsurvey
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public |
A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that are not spatially balanced, select panel samples, measure the amount of spatial balance in a sample, adjust design weights, and more. For additional details, see Dumelle et al. (2023) <doi:10.18637/jss.v105.i03>.
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2025-04-22 |
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r-spscomps
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public |
The systemPipeShiny (SPS) framework comes with many UI and server components. However, installing the whole framework is heavy and takes some time. If you would like to use UI and server components from SPS in your own Shiny apps, do not hesitate to try this package.
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2025-04-22 |
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r-spotifyr
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public |
An R wrapper for pulling data from the 'Spotify' Web API <https://developer.spotify.com/documentation/web-api/> in bulk, or post items on a 'Spotify' user's playlist.
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2025-04-22 |
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r-spocc
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public |
A programmatic interface to many species occurrence data sources, including Global Biodiversity Information Facility ('GBIF'), 'iNaturalist', 'eBird', Integrated Digitized 'Biocollections' ('iDigBio'), 'VertNet', Ocean 'Biogeographic' Information System ('OBIS'), and Atlas of Living Australia ('ALA'). Includes functionality for retrieving species occurrence data, and combining those data.
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2025-04-22 |
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r-splittools
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public |
Fast, lightweight toolkit for data splitting. Data sets can be partitioned into disjoint groups (e.g. into training, validation, and test) or into (repeated) k-folds for subsequent cross-validation. Besides basic splits, the package supports stratified, grouped as well as blocked splitting. Furthermore, cross-validation folds for time series data can be created. See e.g. Hastie et al. (2001) <doi:10.1007/978-0-387-84858-7> for the basic background on data partitioning and cross-validation.
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2025-04-22 |
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r-splm
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public |
ML and GM estimation and diagnostic testing of econometric models for spatial panel data.
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2025-04-22 |
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r-spdl
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public |
Logging functions in 'RcppSpdlog' provide access to the logging functionality from the 'spdlog' 'C++' library. This package offers shorter convenience wrappers for the 'R' functions which match the 'C++' functions, namely via, say, 'spdl::debug()' at the debug level. The actual formatting is done by the 'fmt::format()' function from the 'fmtlib' library (that is also 'std::format()' in 'C++20' or later).
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2025-04-22 |
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r-spei
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public |
A set of functions for computing potential evapotranspiration and several widely used drought indices including the Standardized Precipitation-Evapotranspiration Index (SPEI).
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2025-04-22 |
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r-spechelpers
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public |
Utility functions for spectroscopy. 1. Functions to simulate spectra for use in teaching or testing. 2. Functions to process files created by 'LoggerPro' and 'SpectraSuite' software.
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2025-04-22 |
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r-spatsurv
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public |
Bayesian inference for parametric proportional hazards spatial survival models; flexible spatial survival models. See Benjamin M. Taylor, Barry S. Rowlingson (2017) <doi:10.18637/jss.v077.i04>.
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2025-04-22 |
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r-spatialposition
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public |
Computes spatial position models: the potential model as defined by Stewart (1941) <doi:10.1126/science.93.2404.89> and catchment areas as defined by Reilly (1931) or Huff (1964) <doi:10.2307/1249154>.
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2025-04-22 |
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r-spats
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public |
Analysis of field trial experiments by modelling spatial trends using two-dimensional Penalised spline (P-spline) models.
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2025-04-22 |
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r-sparselda
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public |
Performs sparse linear discriminant analysis for Gaussians and mixture of Gaussian models.
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2025-04-22 |
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r-sparsepca
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public |
Sparse principal component analysis (SPCA) attempts to find sparse weight vectors (loadings), i.e., a weight vector with only a few 'active' (nonzero) values. This approach provides better interpretability for the principal components in high-dimensional data settings. This is, because the principal components are formed as a linear combination of only a few of the original variables. This package provides efficient routines to compute SPCA. Specifically, a variable projection solver is used to compute the sparse solution. In addition, a fast randomized accelerated SPCA routine and a robust SPCA routine is provided. Robust SPCA allows to capture grossly corrupted entries in the data. The methods are discussed in detail by N. Benjamin Erichson et al. (2018) <arXiv:1804.00341>.
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2025-04-22 |
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r-sparsediscrim
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public |
A collection of sparse and regularized discriminant analysis methods intended for small-sample, high-dimensional data sets. The package features the High-Dimensional Regularized Discriminant Analysis classifier from Ramey et al. (2017) <arXiv:1602.01182>. Other classifiers include those from Dudoit et al. (2002) <doi:10.1198/016214502753479248>, Pang et al. (2009) <doi:10.1111/j.1541-0420.2009.01200.x>, and Tong et al. (2012) <doi:10.1093/bioinformatics/btr690>.
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2025-04-22 |
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r-sparr
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public |
Provides functions to estimate kernel-smoothed spatial and spatio-temporal densities and relative risk functions, and perform subsequent inference. Methodological details can be found in the accompanying tutorial: Davies et al. (2018) <DOI:10.1002/sim.7577>.
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2025-04-22 |
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r-spark.sas7bdat
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public |
Read in 'SAS' Data ('.sas7bdat' Files) into 'Apache Spark' from R. 'Apache Spark' is an open source cluster computing framework available at <http://spark.apache.org>. This R package uses the 'spark-sas7bdat' 'Spark' package (<https://spark-packages.org/package/saurfang/spark-sas7bdat>) to import and process 'SAS' data in parallel using 'Spark'. Hereby allowing to execute 'dplyr' statements in parallel on top of 'SAS' data.
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2025-04-22 |
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r-sparklyr.nested
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public |
A 'sparklyr' extension adding the capability to work easily with nested data.
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2025-04-22 |
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r-spacetime
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public |
Classes and methods for spatio-temporal data, including space-time regular lattices, sparse lattices, irregular data, and trajectories; utility functions for plotting data as map sequences (lattice or animation) or multiple time series; methods for spatial and temporal selection and subsetting, as well as for spatial/temporal/spatio-temporal matching or aggregation, retrieving coordinates, print, summary, etc.
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2025-04-22 |
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r-soundgen
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public |
Performs parametric synthesis of sounds with harmonic and noise components such as animal vocalizations or human voice. Also offers tools for audio manipulation and acoustic analysis, including pitch tracking, spectral analysis, audio segmentation, pitch and formant shifting, etc. Includes four interactive web apps for synthesizing and annotating audio, manually correcting pitch contours, and measuring formant frequencies. Reference: Anikin (2019) <doi:10.3758/s13428-018-1095-7>.
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2025-04-22 |
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r-soupx
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public |
Quantify, profile and remove ambient mRNA contamination (the "soup") from droplet based single cell RNA-seq experiments. Implements the method described in Young et al. (2018) <doi:10.1101/303727>.
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2025-04-22 |
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r-sortable
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public |
Enables drag-and-drop behaviour in Shiny apps, by exposing the functionality of the 'SortableJS' <https://sortablejs.github.io/Sortable/> JavaScript library as an 'htmlwidget'. You can use this in Shiny apps and widgets, 'learnr' tutorials as well as R Markdown. In addition, provides a custom 'learnr' question type - 'question_rank()' - that allows ranking questions with drag-and-drop.
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2025-04-22 |
