R-universe search: exports:mean

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 5 hours ago.

geospatial raster spatial vector onetbb proj gdal geos cpp

560 stars 17.65 score 17k scripts 856 dependents

rspatial

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 This package has been superseded by the "terra" package 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 1 days ago.

cpp

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.

openblas

1 stars 17.23 score 33k scripts 12k dependents

bioc

IRanges:Foundation of integer range manipulation in Bioconductor

Provides efficient low-level and highly reusable S4 classes for storing, manipulating and aggregating over annotated ranges of integers. Implements an algebra of range operations, including efficient algorithms for finding overlaps and nearest neighbors. Defines efficient list-like classes for storing, transforming and aggregating large grouped data, i.e., collections of atomic vectors and DataFrames.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation bioconductor-package core-package

22 stars 16.09 score 2.1k scripts 1.8k dependents

bioc

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 Hervé Pagès. Last updated 1 months ago.

infrastructure datarepresentation annotation genomeannotation bioconductor-package core-package u24ca289073

27 stars 15.59 score 538 scripts 1.2k dependents

bioc

BiocGenerics:S4 generic functions used in Bioconductor

The package defines many S4 generic functions used in Bioconductor.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructure bioconductor-package core-package

12 stars 14.22 score 612 scripts 2.2k dependents

projectmosaic

mosaic:Project MOSAIC Statistics and Mathematics Teaching Utilities

Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.

Maintained by Randall Pruim. Last updated 1 years ago.

93 stars 13.32 score 7.2k scripts 7 dependents

bioc

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 Hervé Pagès. Last updated 10 days ago.

infrastructure datarepresentation bioconductor-package core-package openmp

9 stars 12.47 score 79 scripts 1.2k dependents

r-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.

mpfr4 gmp

11.30 score 316 scripts 141 dependents

bioc

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 Hervé Pagès. Last updated 2 months ago.

infrastructure datarepresentation bioconductor-package core-package

5 stars 10.99 score 8 scripts 1.2k dependents

crunch-io

crunch:Crunch.io Data Tools

The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.

Maintained by Greg Freedman Ellis. Last updated 8 days ago.

9 stars 10.47 score 200 scripts 2 dependents

bioc

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.

infrastructure datarepresentation dataimport dimensionreduction preprocessing cpp

57 stars 9.52 score 64 scripts 2 dependents

flr

FLCore:Core Package of FLR, Fisheries Modelling in R

Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.

Maintained by Iago Mosqueira. Last updated 9 days ago.

fisheries flr fisheries-modelling

16 stars 8.78 score 956 scripts 23 dependents

r-forge

distr:Object Oriented Implementation of Distributions

S4-classes and methods for distributions.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

8.77 score 327 scripts 32 dependents

r-hyperspec

hyperSpec:Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

Comfortable ways to work with hyperspectral data sets, i.e. spatially or time-resolved spectra, or spectra with any other kind of information associated with each of the spectra. The spectra can be data as obtained in XRF, UV/VIS, Fluorescence, AES, NIR, IR, Raman, NMR, MS, etc. More generally, any data that is recorded over a discretized variable, e.g. absorbance = f(wavelength), stored as a vector of absorbance values for discrete wavelengths is suitable.

Maintained by Claudia Beleites. Last updated 10 months ago.

data-wrangling hyperspectral imaging infrared nmr raman spectroscopy uv-vis xrf

16 stars 8.10 score 233 scripts 2 dependents

adamlilith

fasterRaster:Faster Raster and Spatial Vector Processing Using 'GRASS GIS'

Processing of large-in-memory/large-on disk rasters and spatial vectors using 'GRASS GIS' <https://grass.osgeo.org/>. Most functions in the 'terra' package are recreated. Processing of medium-sized and smaller spatial objects will nearly always be faster using 'terra' or 'sf', but for large-in-memory/large-on-disk objects, 'fasterRaster' may be faster. To use most of the functions, you must have the stand-alone version (not the 'OSGeoW4' installer version) of 'GRASS GIS' 8.0 or higher.

Maintained by Adam B. Smith. Last updated 2 days ago.

aspect distance fragmentation fragmentation-indices gis grass grass-gis raster raster-projection rasterize slope topography vectorization

57 stars 7.68 score 8 scripts

rapporter

rapportools:Miscellaneous (Stats) Helper Functions with Sane Defaults for Reporting

Helper functions that act as wrappers to more advanced statistical methods with the advantage of having sane defaults for quick reporting.

Maintained by Gergely Daróczi. Last updated 28 days ago.

8 stars 7.50 score 186 scripts 11 dependents

cran

sn:The Skew-Normal and Related Distributions Such as the Skew-t and the SUN

Build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t and the SUN families. For the skew-normal and the skew-t distributions, statistical methods are provided for data fitting and model diagnostics, in the univariate and the multivariate case.

Maintained by Adelchi Azzalini. Last updated 2 years ago.

3 stars 7.44 score 92 dependents

bioc

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.

software infrastructure datarepresentation

1 stars 6.62 score 39 scripts 12 dependents

spkaluzny

splus2R:Supplemental S-PLUS Functionality in R

Currently there are many functions in S-PLUS that are missing in R. To facilitate the conversion of S-PLUS packages to R packages, this package provides some missing S-PLUS functionality in R.

Maintained by Stephen Kaluzny. Last updated 1 years ago.

1 stars 6.56 score 82 scripts 30 dependents

bioc

oligoClasses:Classes for high-throughput arrays supported by oligo and crlmm

This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages.

Maintained by Benilton Carvalho. Last updated 5 months ago.

infrastructure

5.86 score 93 scripts 17 dependents

quantsulting

ghyp:Generalized Hyperbolic Distribution and Its Special Cases

Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management: Concepts, techniques and tools. Princeton University Press, Princeton (2005).

Maintained by Marc Weibel. Last updated 7 months ago.

5.55 score 90 scripts 8 dependents

ropensci

grainchanger:Moving-Window and Direct Data Aggregation

Data aggregation via moving window or direct methods. Aggregate a fine-resolution raster to a grid. The moving window method smooths the surface using a specified function within a moving window of a specified size and shape prior to aggregation. The direct method simply aggregates to the grid using the specified function.

Maintained by Laura Graham. Last updated 2 years ago.

52 stars 5.46 score 28 scripts

centerforstatistics-ugent

xnet:Two-Step Kernel Ridge Regression for Network Predictions

Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 <doi:10.1093/bib/bby095> ).

Maintained by Joris Meys. Last updated 4 years ago.

11 stars 5.30 score 12 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 25 days ago.

archaeology archaeological-science archaeometry compositional-data provenance-studies

5.21 score 26 scripts 1 dependents

jaganmn

flint:Fast Library for Number Theory

An R interface to 'FLINT' <https://flintlib.org/>, a C library for number theory. 'FLINT' extends GNU 'MPFR' <https://www.mpfr.org/> and GNU 'MP' <https://gmplib.org/> with support for operations on standard rings (the integers, the integers modulo n, finite fields, the rational, p-adic, real, and complex numbers) as well as matrices and polynomials over rings. 'FLINT' implements midpoint-radius interval arithmetic, also known as ball arithmetic, in the real and complex numbers, enabling computation in arbitrary precision with rigorous propagation of rounding errors; see Johansson (2017) <doi:10.1109/TC.2017.2690633>. Finally, 'FLINT' provides ball arithmetic implementations of many special mathematical functions, with high coverage of reference works such as the NIST Digital Library of Mathematical Functions <https://dlmf.nist.gov/>. The R interface defines S4 classes, generic functions, and methods for representation and basic operations as well as plain R functions mirroring and vectorizing entry points in the C library.

Maintained by Mikael Jagan. Last updated 5 days ago.

flint mpfr4 gmp

5 stars 5.11 score 20 scripts

spkaluzny

splusTimeDate:Times and Dates from 'S-PLUS'

A collection of classes and methods for working with times and dates. The code was originally available in 'S-PLUS'.

Maintained by Stephen Kaluzny. Last updated 2 months ago.

datetime

4.94 score 58 scripts 2 dependents

bioc

BufferedMatrix:A matrix data storage object held in temporary files

A tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data.

Maintained by Ben Bolstad. Last updated 3 months ago.

infrastructure

4.73 score 6 scripts 1 dependents

bioc

soGGi:Visualise ChIP-seq, MNase-seq and motif occurrence as aggregate plots Summarised Over Grouped Genomic Intervals

The soGGi package provides a toolset to create genomic interval aggregate/summary plots of signal or motif occurence from BAM and bigWig files as well as PWM, rlelist, GRanges and GAlignments Bioconductor objects. soGGi allows for normalisation, transformation and arithmetic operation on and between summary plot objects as well as grouping and subsetting of plots by GRanges objects and user supplied metadata. Plots are created using the GGplot2 libary to allow user defined manipulation of the returned plot object. Coupled together, soGGi features a broad set of methods to visualise genomics data in the context of groups of genomic intervals such as genes, superenhancers and transcription factor binding events.

Maintained by Tom Carroll. Last updated 5 months ago.

sequencing chipseq coverage

4.49 score 51 scripts 1 dependents

cran

NADA:Nondetects and Data Analysis for Environmental Data

Contains methods described by Dennis Helsel in his book "Nondetects And Data Analysis: Statistics for Censored Environmental Data".

Maintained by Lopaka Lee. Last updated 5 years ago.

2 stars 4.45 score 14 dependents

martinbladt

matrixdist:Statistics for Matrix Distributions

Tools for phase-type distributions including the following variants: continuous, discrete, multivariate, in-homogeneous, right-censored, and regression. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided for all models. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996). Fitting phase-type distributions via the EM algorithm, Olsson, M. (1996). Estimation of phase-type distributions from censored data, Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60>, Albrecher, H., Bladt, M., & Yslas, J. (2022) <doi:10.1111/sjos.12505>, Albrecher, H., Bladt, M., Bladt, M., & Yslas, J. (2022) <doi:10.1016/j.insmatheco.2022.08.001>, Bladt, M., & Yslas, J. (2022) <doi:10.1080/03461238.2022.2097019>, Bladt, M. (2022) <doi:10.1017/asb.2021.40>, Bladt, M. (2023) <doi:10.1080/10920277.2023.2167833>, Albrecher, H., Bladt, M., & Mueller, A. (2023) <doi:10.1515/demo-2022-0153>, Bladt, M. & Yslas, J. (2023) <doi:10.1016/j.insmatheco.2023.02.008>.

Maintained by Martin Bladt. Last updated 30 days ago.

openblas cpp openmp

1 stars 4.00 score 2 scripts

spkaluzny

splusTimeSeries:Time Series from 'S-PLUS'

A collection of classes and methods for working with indexed rectangular data. The index values can be calendar (timeSeries class) or numeric (signalSeries class). Methods are included for aggregation, alignment, merging, and summaries. The code was originally available in 'S-PLUS'.

Maintained by Stephen Kaluzny. Last updated 6 months ago.

data-structures time-series

3.95 score 20 scripts 1 dependents

clobatofern95

GPUmatrix:Basic Linear Algebra with GPU

GPUs are great resources for data analysis, especially in statistics and linear algebra. Unfortunately, very few packages connect R to the GPU, and none of them are transparent enough to run the computations on the GPU without substantial changes to the code. The maintenance of these packages is cumbersome: several of the earlier attempts have been removed from their respective repositories. It would be desirable to have a properly maintained R package that takes advantage of the GPU with minimal changes to the existing code. We have developed the GPUmatrix package (available on CRAN). GPUmatrix mimics the behavior of the Matrix package and extends R to use the GPU for computations. It includes single(FP32) and double(FP64) precision data types, and provides support for sparse matrices. It is easy to learn, and requires very few code changes to perform the operations on the GPU. GPUmatrix relies on either the Torch or Tensorflow R packages to perform the GPU operations. We have demonstrated its usefulness for several statistical applications and machine learning applications: non-negative matrix factorization, logistic regression and general linear models. We have also included a comparison of GPU and CPU performance on different matrix operations.

Maintained by Cesar Lobato-Fernandez. Last updated 1 years ago.

3.93 score 57 scripts 1 dependents

reidt03

RadOnc:Analytical Tools for Radiation Oncology

Designed for the import, analysis, and visualization of dosimetric and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume histogram information from multiple treatment planning system platforms and 3D structural representations and dosimetric information from 'DICOM-RT' files. These tools also enable subsequent visualization and statistical analysis of these data.

Maintained by Reid F. Thompson. Last updated 2 months ago.

8 stars 3.78 score 19 scripts

lawremi

rsolr:R to Solr Interface

A comprehensive R API for querying Apache Solr databases. A Solr core is represented as a data frame or list that supports Solr-side filtering, sorting, transformation and aggregation, all through the familiar base R API. Queries are processed lazily, i.e., a query is only sent to the database when the data are required.

Maintained by Michael Lawrence. Last updated 3 years ago.

9 stars 3.65 score 6 scripts

r-forge

distrEllipse:S4 Classes for Elliptically Contoured Distributions

Distribution (S4-)classes for elliptically contoured distributions (based on package 'distr').

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

3.46 score 18 scripts

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

haghbinh

ReMFPCA:Regularized Multivariate Functional Principal Component Analysis

Methods and tools for implementing regularized multivariate functional principal component analysis ('ReMFPCA') for multivariate functional data whose variables might be observed over different dimensional domains. 'ReMFPCA' is an object-oriented interface leveraging the extensibility and scalability of R6. It employs a parameter vector to control the smoothness of each functional variable. By incorporating smoothness constraints as penalty terms within a regularized optimization framework, 'ReMFPCA' generates smooth multivariate functional principal components, offering a concise and interpretable representation of the data. For detailed information on the methods and techniques used in 'ReMFPCA', please refer to Haghbin et al. (2023) <doi:10.48550/arXiv.2306.13980>.

Maintained by Hossein Haghbin. Last updated 2 months ago.

4 stars 3.30 score

r-forge

distrRmetrics:Distribution Classes for Distributions from Rmetrics

S4-distribution classes based on package distr for distributions from packages 'fBasics' and 'fGarch'.

Maintained by Peter Ruckdeschel. Last updated 2 months ago.

3.20 score 7 scripts

gillian-earthscope

IRISSeismic:Classes and Methods for Seismic Data Analysis

Provides classes and methods for seismic data analysis. The base classes and methods are inspired by the python code found in the 'ObsPy' python toolbox <https://github.com/obspy/obspy>. Additional classes and methods support data returned by web services provided by EarthScope. <https://service.earthscope.org/>.

Maintained by Gillian Sharer. Last updated 4 months ago.

3.18 score 50 scripts 1 dependents

certe-medical-epidemiology

certestats:A Certe R Package for Statistical Modelling

A Certe R Package for early-warning, applying statistical modelling (such as creating machine learning models), QC rules and distribution analysis. This package is part of the 'certedata' universe.

Maintained by Matthijs S. Berends. Last updated 5 months ago.

statistics

3.02 score 1 scripts 1 dependents

garciagarjose

IntervalQuestionStat:Tools to Deal with Interval-Valued Responses in Questionnaires

A user-friendly toolbox for doing the statistical analysis of interval-valued responses in questionnaires measuring intrinsically imprecise human attributes or features (attitudes, perceptions, opinions, feelings, etc.). In particular, this package provides S4 classes, methods, and functions in order to compute basic arithmetic and statistical operations with interval-valued data; prepare customized plots; associate each interval-valued response to its equivalent Likert-type and visual analogue scales answers through the minimum theta-distance and the mid-point criteria; analyze the reliability of respondents' answers from the internal consistency point of view by means of Cronbach's alpha coefficient; and simulate interval-valued responses in this type of questionnaires. The package also incorporates some real-life data that can be used to illustrate its working with several non-trivial reproducible examples. The methodology used in this package is based in many theoretical and applied publications from SMIRE+CoDiRE (Statistical Methods with Imprecise Random Elements and Comparison of Distributions of Random Elements) Research Group (<https://bellman.ciencias.uniovi.es/smire+codire/>) from the University of Oviedo (Spain).

Maintained by José García-García. Last updated 1 years ago.

2 stars 3.00 score 1 scripts

multimeric

HistDat:Summary Statistics for Histogram/Count Data

In some cases you will have data in a histogram format, where you have a vector of all possible observations, and a vector of how many times each observation appeared. You could expand this into a single 1D vector, but this may not be advisable if the counts are extremely large. 'HistDat' allows for the calculation of summary statistics without the need for expanding your data.

Maintained by Michael Milton. Last updated 4 years ago.

1 stars 3.00 score 7 scripts

cran

biganalytics:Utilities for 'big.matrix' Objects from Package 'bigmemory'

Extend the 'bigmemory' package with various analytics. Functions 'bigkmeans' and 'binit' may also be used with native R objects. For 'tapply'-like functions, the bigtabulate package may also be helpful. For linear algebra support, see 'bigalgebra'. For mutex (locking) support for advanced shared-memory usage, see 'synchronicity'.

Maintained by Michael J. Kane. Last updated 1 years ago.

cpp

1 stars 2.08 score 4 dependents

apedrods

MAINT.Data:Model and Analyse Interval Data

Implements methodologies for modelling interval data by Normal and Skew-Normal distributions, considering appropriate parameterizations of the variance-covariance matrix that takes into account the intrinsic nature of interval data, and lead to four different possible configuration structures. The Skew-Normal parameters can be estimated by maximum likelihood, while Normal parameters may be estimated by maximum likelihood or robust trimmed maximum likelihood methods.

Maintained by Pedro Duarte Silva. Last updated 2 years ago.

openblas cpp

1.15 score 14 scripts

guangbaog

DTSR:Distributed Trimmed Scores Regression for Handling Missing Data

Provides functions for handling missing data using Distributed Trimmed Scores Regression and other imputation methods. It includes facilities for data imputation, evaluation metrics, and clustering analysis. It is designed to work in distributed computing environments to handle large datasets efficiently. The philosophy of the package is described in Guo G. (2024) <doi:10.1080/03610918.2022.2091779>.

Maintained by Guangbao Guo. Last updated 5 months ago.

1.00 score