Showing 42 of total 42 results (show query)
stan-dev
posterior:Tools for Working with Posterior Distributions
Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Maintained by Paul-Christian Bürkner. Last updated 1 days ago.
168 stars 16.21 score 3.3k scripts 346 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.
infrastructuredatarepresentationbioconductor-packagecore-package
22 stars 16.09 score 2.1k scripts 1.8k dependentsbioc
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 Hervé Pagès. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
18 stars 16.05 score 1.0k scripts 1.9k dependentsbioc
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.
infrastructurebioconductor-packagecore-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 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 Hervé Pagès. Last updated 11 days ago.
infrastructuredatarepresentationbioconductor-packagecore-packageopenmp
9 stars 12.47 score 79 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 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
vigou3
actuar:Actuarial Functions and Heavy Tailed Distributions
Functions and data sets for actuarial science: modeling of loss distributions; risk theory and ruin theory; simulation of compound models, discrete mixtures and compound hierarchical models; credibility theory. Support for many additional probability distributions to model insurance loss size and frequency: 23 continuous heavy tailed distributions; the Poisson-inverse Gaussian discrete distribution; zero-truncated and zero-modified extensions of the standard discrete distributions. Support for phase-type distributions commonly used to compute ruin probabilities. Main reference: <doi:10.18637/jss.v025.i07>. Implementation of the Feller-Pareto family of distributions: <doi:10.18637/jss.v103.i06>.
Maintained by Vincent Goulet. Last updated 3 months ago.
12 stars 9.44 score 732 scripts 35 dependents
eagerai
fastai:Interface to 'fastai'
The 'fastai' <https://docs.fast.ai/index.html> library simplifies training fast and accurate neural networks using modern best practices. It is based on research in to deep learning best practices undertaken at 'fast.ai', including 'out of the box' support for vision, text, tabular, audio, time series, and collaborative filtering models.
Maintained by Turgut Abdullayev. Last updated 12 months ago.
audiocollaborative-filteringdarknetdarknet-image-classificationfastaimedicalobject-detectiontabulartextvision
118 stars 9.40 score 76 scripts
robinhankin
elliptic:Weierstrass and Jacobi Elliptic Functions
A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions.
Maintained by Robin K. S. Hankin. Last updated 24 days ago.
3 stars 9.31 score 54 scripts 79 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.
fisheriesflrfisheries-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
martin3141
spant:MR Spectroscopy Analysis Tools
Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.
Maintained by Martin Wilson. Last updated 1 days ago.
brainmrimrsmrshubspectroscopyfortran
25 stars 8.52 score 81 scripts
tomasfryda
h2o:R Interface for the 'H2O' Scalable Machine Learning Platform
R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Maintained by Tomas Fryda. Last updated 1 years ago.
3 stars 8.20 score 7.8k scripts 11 dependents
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 29 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
meireles
spectrolab:Class and Methods for Spectral Data
Input/Output, processing and visualization of spectra taken with different spectrometers, including SVC (Spectra Vista), ASD and PSR (Spectral Evolution). Implements an S3 class spectra that other packages can build on. Provides methods to access, plot, manipulate, splice sensor overlap, vector normalize and smooth spectra.
Maintained by Jose Eduardo Meireles. Last updated 3 months ago.
16 stars 7.39 score 256 scriptsr-forge
distrEx:Extensions of Package 'distr'
Extends package 'distr' by functionals, distances, and conditional distributions.
Maintained by Matthias Kohl. Last updated 2 months ago.
6.64 score 107 scripts 17 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
tidyfun
tf:S3 Classes and Methods for Tidy Functional Data
Defines S3 vector data types for vectors of functional data (grid-based, spline-based or functional principal components-based) with all arithmetic and summary methods, derivation, integration and smoothing, plotting, data import and export, and data wrangling, such as re-evaluating, subsetting, sub-assigning, zooming into sub-domains, or extracting functional features like minima/maxima and their locations. The implementation allows including such vectors in data frames for joint analysis of functional and scalar variables.
Maintained by Fabian Scheipl. Last updated 5 hours ago.
7 stars 6.14 score 13 scripts 2 dependents
fbartos
BayesTools:Tools for Bayesian Analyses
Provides tools for conducting Bayesian analyses and Bayesian model averaging (Kass and Raftery, 1995, <doi:10.1080/01621459.1995.10476572>, Hoeting et al., 1999, <doi:10.1214/ss/1009212519>). The package contains functions for creating a wide range of prior distribution objects, mixing posterior samples from 'JAGS' and 'Stan' models, plotting posterior distributions, and etc... The tools for working with prior distribution span from visualization, generating 'JAGS' and 'bridgesampling' syntax to basic functions such as rng, quantile, and distribution functions.
Maintained by František Bartoš. Last updated 2 months ago.
7 stars 6.06 score 17 scripts 3 dependents
jcfaria
fdth:Frequency Distribution Tables, Histograms and Polygons
Perform frequency distribution tables, associated histograms and polygons from vector, data.frame and matrix objects for numerical and categorical variables.
Maintained by José C. Faria. Last updated 1 years ago.
2 stars 5.93 score 107 scriptscran
circular:Circular Statistics
Circular Statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.
Maintained by Eduardo García-Portugués. Last updated 7 months ago.
7 stars 5.71 score 40 dependents
bayesiandemography
rvec:Vector Representing a Random Variable
Random vectors, called rvecs. An rvec holds multiple draws, but tries to behave like a standard R vector, including working well in data frames. Rvecs are useful for working with output from a simulation or a Bayesian analysis.
Maintained by John Bryant. Last updated 6 months ago.
2 stars 5.46 score 24 scripts 2 dependentscran
ftsa:Functional Time Series Analysis
Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.
Maintained by Han Lin Shang. Last updated 1 months ago.
6 stars 4.61 score 10 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 scriptsrobinhankin
cmvnorm:The Complex Multivariate Gaussian Distribution
Various utilities for the complex multivariate Gaussian distribution and complex Gaussian processes.
Maintained by Robin K. S. Hankin. Last updated 4 months ago.
2 stars 4.60 score 7 scriptscran
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
jmcurran
Bolstad:Functions for Elementary Bayesian Inference
A set of R functions and data sets for the book Introduction to Bayesian Statistics, Bolstad, W.M. (2017), John Wiley & Sons ISBN 978-1-118-09156-2.
Maintained by James Curran. Last updated 5 months ago.
4.09 score 93 scripts
jrvanderdoes
fChange:Functional Change Point Detection and Analysis
Analyze functional data and its change points. Includes functionality to store and process data, summarize and validate assumptions, characterize and perform inference of change points, and provide visualizations. Data is stored as discretely collected observations without requiring the selection of basis functions. For more details see chapter 8 of Horvath and Rice (2024) <doi:10.1007/978-3-031-51609-2>. Additional papers are forthcoming. Focused works are also included in the documentation of corresponding functions.
Maintained by Jeremy VanderDoes. Last updated 10 hours ago.
1 stars 4.04 score
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
sth1402
DynTxRegime:Methods for Estimating Optimal Dynamic Treatment Regimes
Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.
Maintained by Shannon T. Holloway. Last updated 1 years ago.
2 stars 3.44 score 115 scripts 2 dependents
cran
RSDA:R to Symbolic Data Analysis
Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.
Maintained by Oldemar Rodriguez. Last updated 1 years ago.
1 stars 3.26 score 3 dependentsr-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.
3.02 score 1 scripts 1 dependentscran
ibmdbR:IBM in-Database Analytics for R
Functionality required to efficiently use R with IBM(R) Db2(R) Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2 for z/OS(R) in conjunction with IBM Db2 Analytics Accelerator for z/OS. Many basic and complex R operations are pushed down into the database, which removes the main memory boundary of R and allows to make full use of parallel processing in the underlying database. For executing R-functions in a multi-node environment in parallel the idaTApply() function requires the 'SparkR' package (<https://spark.apache.org/docs/latest/sparkr.html>). The optional 'ggplot2' package is needed for the plot.idaLm() function only.
Maintained by Shaikh Quader. Last updated 1 years ago.
2 stars 3.00 score
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
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.
1.15 score 14 scripts