Showing 51 of total 51 results (show query)
rspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 2 days ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
559 stars 17.64 score 17k scripts 855 dependentsrspatial
raster:Geographic Data Analysis and Modeling
Reading, writing, manipulating, analyzing and modeling of spatial data. This package has been superseded by the "terra" package <https://CRAN.R-project.org/package=terra>.
Maintained by Robert J. Hijmans. Last updated 15 hours ago.
163 stars 17.23 score 58k scripts 562 dependents
r-forge
Matrix:Sparse and Dense Matrix Classes and Methods
A rich hierarchy of sparse and dense matrix classes, including general, symmetric, triangular, and diagonal matrices with numeric, logical, or pattern entries. Efficient methods for operating on such matrices, often wrapping the 'BLAS', 'LAPACK', and 'SuiteSparse' libraries.
Maintained by Martin Maechler. Last updated 19 days ago.
1 stars 17.23 score 33k scripts 12k dependents
quanteda
quanteda:Quantitative Analysis of Textual Data
A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and n-grams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Maintained by Kenneth Benoit. Last updated 3 months ago.
corpusnatural-language-processingquantedatext-analyticsonetbbcpp
851 stars 16.65 score 5.4k scripts 52 dependents
bioc
S4Vectors:Foundation of vector-like and list-like containers in Bioconductor
The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, Factor, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).
Maintained by Hervรฉ Pagรจs. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
18 stars 16.05 score 1.0k scripts 1.9k dependentsbioc
DelayedArray:A unified framework for working transparently with on-disk and in-memory array-like datasets
Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, ordinary arrays and, data frames.
Maintained by Hervรฉ Pagรจs. Last updated 1 months ago.
infrastructuredatarepresentationannotationgenomeannotationbioconductor-packagecore-packageu24ca289073
27 stars 15.59 score 538 scripts 1.2k dependentsbioc
BiocGenerics:S4 generic functions used in Bioconductor
The package defines many S4 generic functions used in Bioconductor.
Maintained by Hervรฉ Pagรจs. Last updated 2 months ago.
infrastructurebioconductor-packagecore-package
12 stars 14.22 score 612 scripts 2.2k dependents
mhahsler
arules:Mining Association Rules and Frequent Itemsets
Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat. Hahsler, Gruen and Hornik (2005) <doi:10.18637/jss.v014.i15>.
Maintained by Michael Hahsler. Last updated 2 months ago.
arulesassociation-rulesfrequent-itemsets
194 stars 13.99 score 3.3k scripts 28 dependentsbioc
phyloseq:Handling and analysis of high-throughput microbiome census data
phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.
Maintained by Paul J. McMurdie. Last updated 5 months ago.
immunooncologysequencingmicrobiomemetagenomicsclusteringclassificationmultiplecomparisongeneticvariability
597 stars 13.90 score 8.4k scripts 37 dependents
richarddmorey
BayesFactor:Computation of Bayes Factors for Common Designs
A suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.
Maintained by Richard D. Morey. Last updated 1 years ago.
132 stars 13.71 score 1.7k scripts 21 dependentsbioc
HDF5Array:HDF5 datasets as array-like objects in R
The HDF5Array package is an HDF5 backend for DelayedArray objects. It implements the HDF5Array, H5SparseMatrix, H5ADMatrix, and TENxMatrix classes, 4 convenient and memory-efficient array-like containers for representing and manipulating either: (1) a conventional (a.k.a. dense) HDF5 dataset, (2) an HDF5 sparse matrix (stored in CSR/CSC/Yale format), (3) the central matrix of an h5ad file (or any matrix in the /layers group), or (4) a 10x Genomics sparse matrix. All these containers are DelayedArray extensions and thus support all operations (delayed or block-processed) supported by DelayedArray objects.
Maintained by Hervรฉ Pagรจs. Last updated 9 days ago.
infrastructuredatarepresentationdataimportsequencingrnaseqcoverageannotationgenomeannotationsinglecellimmunooncologybioconductor-packagecore-packageu24ca289073
12 stars 13.20 score 844 scripts 126 dependents
cvxgrp
CVXR:Disciplined Convex Optimization
An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Maintained by Anqi Fu. Last updated 5 months ago.
207 stars 12.89 score 768 scripts 51 dependents
spedygiorgio
markovchain:Easy Handling Discrete Time Markov Chains
Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.
Maintained by Giorgio Alfredo Spedicato. Last updated 5 months ago.
ctmcdtmcmarkov-chainmarkov-modelr-programmingrcppopenblascpp
104 stars 12.78 score 712 scripts 4 dependentsbioc
MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
Maintained by Laurent Gatto. Last updated 14 days ago.
immunooncologyinfrastructureproteomicsmassspectrometryqualitycontroldataimportbioconductorbioinformaticsmass-spectrometryproteomics-datavisualisationcpp
131 stars 12.76 score 772 scripts 36 dependentsbioc
SparseArray:High-performance sparse data representation and manipulation in R
The SparseArray package provides array-like containers for efficient in-memory representation of multidimensional sparse data in R (arrays and matrices). The package defines the SparseArray virtual class and two concrete subclasses: COO_SparseArray and SVT_SparseArray. Each subclass uses its own internal representation of the nonzero multidimensional data: the "COO layout" and the "SVT layout", respectively. SVT_SparseArray objects mimic as much as possible the behavior of ordinary matrix and array objects in base R. In particular, they suppport most of the "standard matrix and array API" defined in base R and in the matrixStats package from CRAN.
Maintained by Hervรฉ Pagรจs. Last updated 10 days ago.
infrastructuredatarepresentationbioconductor-packagecore-packageopenmp
9 stars 12.47 score 79 scripts 1.2k dependentsbioc
BiocSingular:Singular Value Decomposition for Bioconductor Packages
Implements exact and approximate methods for singular value decomposition and principal components analysis, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Where possible, parallelization is achieved using the BiocParallel framework.
Maintained by Aaron Lun. Last updated 5 months ago.
softwaredimensionreductionprincipalcomponentbioconductor-packagehuman-cell-atlassingular-value-decompositioncpp
7 stars 12.10 score 1.2k scripts 103 dependents
rudjer
SparseM:Sparse Linear Algebra
Some basic linear algebra functionality for sparse matrices is provided: including Cholesky decomposition and backsolving as well as standard R subsetting and Kronecker products.
Maintained by Roger Koenker. Last updated 8 months ago.
3 stars 11.47 score 306 scripts 1.5k dependentsr-forge
Rmpfr:Interface R to MPFR - Multiple Precision Floating-Point Reliable
Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
Maintained by Martin Maechler. Last updated 4 months ago.
11.30 score 316 scripts 141 dependentsbioc
S4Arrays:Foundation of array-like containers in Bioconductor
The S4Arrays package defines the Array virtual class to be extended by other S4 classes that wish to implement a container with an array-like semantic. It also provides: (1) low-level functionality meant to help the developer of such container to implement basic operations like display, subsetting, or coercion of their array-like objects to an ordinary matrix or array, and (2) a framework that facilitates block processing of array-like objects (typically on-disk objects).
Maintained by Hervรฉ Pagรจs. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
5 stars 10.99 score 8 scripts 1.2k dependents
eddelbuettel
nanotime:Nanosecond-Resolution Time Support for R
Full 64-bit resolution date and time functionality with nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type. Three additional classes offer interval, period and duration functionality for nanosecond-resolution timestamps.
Maintained by Dirk Eddelbuettel. Last updated 2 months ago.
datetimedatetimesnanosecond-resolutionnanosecondscpp
53 stars 10.91 score 134 scripts 17 dependents
zdebruine
RcppML:Rcpp Machine Learning Library
Fast machine learning algorithms including matrix factorization and divisive clustering for large sparse and dense matrices.
Maintained by Zach DeBruine. Last updated 2 years ago.
clusteringmatrix-factorizationnmfrcpprcppeigensparse-matrixcppopenmp
107 stars 10.66 score 125 scripts 50 dependents
wrathematics
float:32-Bit Floats
R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.
Maintained by Drew Schmidt. Last updated 19 days ago.
float-matrixhpclinear-algebramatrixfortranopenblasopenmp
46 stars 10.53 score 228 scripts 42 dependents
robinhankin
Brobdingnag:Very Large Numbers in R
Very large numbers in R. Real numbers are held using their natural logarithms, plus a logical flag indicating sign. Functionality for complex numbers is also provided. The package includes a vignette that gives a step-by-step introduction to using S4 methods.
Maintained by Robin K. S. Hankin. Last updated 7 months ago.
5 stars 9.92 score 77 scripts 70 dependentsbioc
matter:Out-of-core statistical computing and signal processing
Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.
Maintained by Kylie A. Bemis. Last updated 4 months ago.
infrastructuredatarepresentationdataimportdimensionreductionpreprocessingcpp
57 stars 9.52 score 64 scripts 2 dependents
edzer
intervals:Tools for Working with Points and Intervals
Tools for working with and comparing sets of points and intervals.
Maintained by Edzer Pebesma. Last updated 7 months ago.
11 stars 9.50 score 122 scripts 98 dependents
reinhardfurrer
spam:SPArse Matrix
Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.
Maintained by Reinhard Furrer. Last updated 2 months ago.
1 stars 9.36 score 420 scripts 439 dependents
david-cortes
MatrixExtra:Extra Methods for Sparse Matrices
Extends sparse matrix and vector classes from the 'Matrix' package by providing: (a) Methods and operators that work natively on CSR formats (compressed sparse row, a.k.a. 'RsparseMatrix') such as slicing/sub-setting, assignment, rbind(), mathematical operators for CSR and COO such as addition ("+") or sqrt(), and methods such as diag(); (b) Multi-threaded matrix multiplication and cross-product for many <sparse, dense> types, including the 'float32' type from 'float'; (c) Coercion methods between pairs of classes which are not present in 'Matrix', such as 'dgCMatrix' -> 'ngRMatrix', as well as convenience conversion functions; (d) Utility functions for sparse matrices such as sorting the indices or removing zero-valued entries; (e) Fast transposes that work by outputting in the opposite storage format; (f) Faster replacements for many 'Matrix' methods for all sparse types, such as slicing and elementwise multiplication. (g) Convenience functions for sparse objects, such as 'mapSparse' or a shorter 'show' method.
Maintained by David Cortes. Last updated 9 months ago.
csrsparse-matrixopenblascppopenmp
20 stars 9.08 score 84 scripts 29 dependents
asl
svd:Interfaces to Various State-of-Art SVD and Eigensolvers
R bindings to SVD and eigensolvers (PROPACK, nuTRLan).
Maintained by Anton Korobeynikov. Last updated 3 months ago.
27 stars 8.80 score 244 scripts 30 dependentsbioc
ScaledMatrix:Creating a DelayedMatrix of Scaled and Centered Values
Provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale() function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.
Maintained by Aaron Lun. Last updated 2 months ago.
8.44 score 10 scripts 105 dependents
symengine
symengine:Interface to the 'SymEngine' Library
Provides an R interface to 'SymEngine' <https://github.com/symengine/>, a standalone 'C++' library for fast symbolic manipulation. The package has functionalities for symbolic computation like calculating exact mathematical expressions, solving systems of linear equations and code generation.
Maintained by Jialin Ma. Last updated 1 years ago.
26 stars 8.20 score 33 scripts 10 dependents
cran
timeSeries:Financial Time Series Objects (Rmetrics)
'S4' classes and various tools for financial time series: Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions.
Maintained by Georgi N. Boshnakov. Last updated 6 months ago.
2 stars 7.89 score 146 dependents
rikenbit
rTensor:Tools for Tensor Analysis and Decomposition
A set of tools for creation, manipulation, and modeling of tensors with arbitrary number of modes. A tensor in the context of data analysis is a multidimensional array. rTensor does this by providing a S4 class 'Tensor' that wraps around the base 'array' class. rTensor provides common tensor operations as methods, including matrix unfolding, summing/averaging across modes, calculating the Frobenius norm, and taking the inner product between two tensors. Familiar array operations are overloaded, such as index subsetting via '[' and element-wise operations. rTensor also implements various tensor decomposition, including CP, GLRAM, MPCA, PVD, and Tucker. For tensors with 3 modes, rTensor also implements transpose, t-product, and t-SVD, as defined in Kilmer et al. (2013). Some auxiliary functions include the Khatri-Rao product, Kronecker product, and the Hadamard product for a list of matrices.
Maintained by Koki Tsuyuzaki. Last updated 2 years ago.
6 stars 7.65 score 278 scripts 30 dependents
bnprks
BPCells:Single Cell Counts Matrices to PCA
> Efficient operations for single cell ATAC-seq fragments and RNA counts matrices. Interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.
Maintained by Benjamin Parks. Last updated 2 months ago.
184 stars 7.48 score 172 scriptsrobinhankin
onion:Octonions and Quaternions
Quaternions and Octonions are four- and eight- dimensional extensions of the complex numbers. They are normed division algebras over the real numbers and find applications in spatial rotations (quaternions), and string theory and relativity (octonions). The quaternions are noncommutative and the octonions nonassociative. See the package vignette for more details.
Maintained by Robin K. S. Hankin. Last updated 1 months ago.
6 stars 7.27 score 43 scripts 3 dependentsbioc
ResidualMatrix:Creating a DelayedMatrix of Regression Residuals
Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.
Maintained by Aaron Lun. Last updated 3 months ago.
softwaredatarepresentationregressionbatcheffectexperimentaldesign
1 stars 6.83 score 6 scripts 10 dependentsbioc
BumpyMatrix:Bumpy Matrix of Non-Scalar Objects
Implements the BumpyMatrix class and several subclasses for holding non-scalar objects in each entry of the matrix. This is akin to a ragged array but the raggedness is in the third dimension, much like a bumpy surface - hence the name. Of particular interest is the BumpyDataFrameMatrix, where each entry is a Bioconductor data frame. This allows us to naturally represent multivariate data in a format that is compatible with two-dimensional containers like the SummarizedExperiment and MultiAssayExperiment objects.
Maintained by Aaron Lun. Last updated 3 months ago.
softwareinfrastructuredatarepresentation
1 stars 6.62 score 39 scripts 12 dependents
shabbychef
madness:Automatic Differentiation of Multivariate Operations
An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.
Maintained by Steven E. Pav. Last updated 4 years ago.
31 stars 6.59 score 28 scripts 3 dependents
r-forge
RandVar:Implementation of Random Variables
Implements random variables by means of S4 classes and methods.
Maintained by Matthias Kohl. Last updated 2 months ago.
6.03 score 43 scripts 7 dependents
dpmcsuss
iGraphMatch:Tools for Graph Matching
Versatile tools and data for graph matching analysis with various forms of prior information that supports working with 'igraph' objects, matrix objects, or lists of either.
Maintained by Daniel Sussman. Last updated 11 months ago.
graph-algorithmsgraph-matchingcpp
9 stars 5.65 score 9 scripts
tesselle
nexus:Sourcing Archaeological Materials by Chemical Composition
Exploration and analysis of compositional data in the framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package provides tools for chemical fingerprinting and source tracking of ancient materials.
Maintained by Nicolas Frerebeau. Last updated 24 days ago.
archaeologyarchaeological-sciencearchaeometrycompositional-dataprovenance-studies
5.21 score 26 scripts 1 dependentsbioc
zitools:Analysis of zero-inflated count data
zitools allows for zero inflated count data analysis by either using down-weighting of excess zeros or by replacing an appropriate proportion of excess zeros with NA. Through overloading frequently used statistical functions (such as mean, median, standard deviation), plotting functions (such as boxplots or heatmap) or differential abundance tests, it allows a wide range of downstream analyses for zero-inflated data in a less biased manner. This becomes applicable in the context of microbiome analyses, where the data is often overdispersed and zero-inflated, therefore making data analysis extremly challenging.
Maintained by Carlotta Meyring. Last updated 5 months ago.
softwarestatisticalmethodmicrobiome
4.60 score 6 scripts
yunuuuu
BPCellsArray:Using BPCells as a DelayedArray Backend
Implements a DelayedArray backend for reading and writing arrays in the BPCells storage layout. The resulting BPCells*Arrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.
Maintained by Yun Peng. Last updated 8 months ago.
softwaredataimportdatarepresentationinfrastructuresingle-cell
7 stars 4.32 scorecran
Mercator:Clustering and Visualizing Distance Matrices
Defines the classes used to explore, cluster and visualize distance matrices, especially those arising from binary data. See Abrams and colleagues, 2021, <doi:10.1093/bioinformatics/btab037>.
Maintained by Kevin R. Coombes. Last updated 5 months ago.
4.26 score 1 dependents
mbertolacci
WoodburyMatrix:Fast Matrix Operations via the Woodbury Matrix Identity
A hierarchy of classes and methods for manipulating matrices formed implicitly from the sums of the inverses of other matrices, a situation commonly encountered in spatial statistics and related fields. Enables easy use of the Woodbury matrix identity and the matrix determinant lemma to allow computation (e.g., solving linear systems) without having to form the actual matrix. More information on the underlying linear algebra can be found in Harville, D. A. (1997) <doi:10.1007/b98818>.
Maintained by Michael Bertolacci. Last updated 2 years ago.
3 stars 4.22 score 11 scripts
geobosh
mcompanion:Objects and Methods for Multi-Companion Matrices
Provides a class for multi-companion matrices with methods for arithmetic and factorization. A method for generation of multi-companion matrices with prespecified spectral properties is provided, as well as some utilities for periodically correlated and multivariate time series models. See Boshnakov (2002) <doi:10.1016/S0024-3795(01)00475-X> and Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>.
Maintained by Georgi N. Boshnakov. Last updated 1 years ago.
eigen-vector-decompositionmatricesperiodictime-series
4.05 score 37 scripts 2 dependents
dmurdoch
orientlib:Support for Orientation Data
Representations, conversions and display of orientation SO(3) data. See the orientlib help topic for details.
Maintained by Duncan Murdoch. Last updated 2 years ago.
1 stars 3.31 score 20 scripts
adamkocsis
via:Virtual Arrays
The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.
Maintained by Adam T. Kocsis. Last updated 2 years ago.
3 stars 3.18 score 8 scripts
bpfaff
gogarch:Generalized Orthogonal GARCH (GO-GARCH) Models
Provision of classes and methods for estimating generalized orthogonal GARCH models. This is an alternative approach to CC-GARCH models in the context of multivariate volatility modeling.
Maintained by Bernhard Pfaff. Last updated 3 years ago.
1.26 score 18 scripts