Showing 26 of total 26 results (show query)
r-lib
httr2:Perform HTTP Requests and Process the Responses
Tools for creating and modifying HTTP requests, then performing them and processing the results. 'httr2' is a modern re-imagining of 'httr' that uses a pipe-based interface and solves more of the problems that API wrapping packages face.
Maintained by Hadley Wickham. Last updated 2 days ago.
246 stars 17.64 score 1.9k scripts 1.1k dependents
hojsgaard
doBy:Groupwise Statistics, LSmeans, Linear Estimates, Utilities
Utility package containing: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear estimates. 3) Restrict functions to a smaller domain. 4) Miscellaneous other utilities.
Maintained by Søren Højsgaard. Last updated 2 days ago.
1 stars 14.99 score 3.2k scripts 948 dependents
bioc
xcms:LC-MS and GC-MS Data Analysis
Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.
Maintained by Steffen Neumann. Last updated 15 days ago.
immunooncologymassspectrometrymetabolomicsbioconductorfeature-detectionmass-spectrometrypeak-detectioncpp
196 stars 14.31 score 984 scripts 11 dependents
tidyverts
fabletools:Core Tools for Packages in the 'fable' Framework
Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Maintained by Mitchell OHara-Wild. Last updated 2 months ago.
91 stars 12.18 score 396 scripts 18 dependentsbioc
GenomicDataCommons:NIH / NCI Genomic Data Commons Access
Programmatically access the NIH / NCI Genomic Data Commons RESTful service.
Maintained by Sean Davis. Last updated 2 months ago.
dataimportsequencingapi-clientbioconductorbioinformaticscancercore-servicesdata-sciencegenomicsncitcgavignette
87 stars 11.94 score 238 scripts 12 dependents
rspatial
dismo:Species Distribution Modeling
Methods for species distribution modeling, that is, predicting the environmental similarity of any site to that of the locations of known occurrences of a species.
Maintained by Robert J. Hijmans. Last updated 4 months ago.
25 stars 11.88 score 2.8k scripts 21 dependents
aphalo
photobiology:Photobiological Calculations
Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Maintained by Pedro J. Aphalo. Last updated 16 days ago.
lightphotobiologyquantificationr4photobiology-suiteradiationspectrasun-position
4 stars 9.35 score 604 scripts 12 dependents
spatstat
spatstat.model:Parametric Statistical Modelling and Inference for the 'spatstat' Family
Functionality for parametric statistical modelling and inference for spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Supports parametric modelling, formal statistical inference, and model validation. Parametric models include Poisson point processes, Cox point processes, Neyman-Scott cluster processes, Gibbs point processes and determinantal point processes. Models can be fitted to data using maximum likelihood, maximum pseudolikelihood, maximum composite likelihood and the method of minimum contrast. Fitted models can be simulated and predicted. Formal inference includes hypothesis tests (quadrat counting tests, Cressie-Read tests, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, ANOVA tests of fitted models, adjusted composite likelihood ratio test, envelope tests, Dao-Genton test, balanced independent two-stage test), confidence intervals for parameters, and prediction intervals for point counts. Model validation techniques include leverage, influence, partial residuals, added variable plots, diagnostic plots, pseudoscore residual plots, model compensators and Q-Q plots.
Maintained by Adrian Baddeley. Last updated 7 days ago.
analysis-of-variancecluster-processconfidence-intervalscox-processdeterminantal-point-processesgibbs-processinfluenceleveragemodel-diagnosticsneyman-scottparameter-estimationpoisson-processspatial-analysisspatial-modellingspatial-point-processesstatistical-inference
5 stars 9.09 score 6 scripts 46 dependents
swihart
rmutil:Utilities for Nonlinear Regression and Repeated Measurements Models
A toolkit of functions for nonlinear regression and repeated measurements not to be used by itself but called by other Lindsey packages such as 'gnlm', 'stable', 'growth', 'repeated', and 'event' (available at <https://www.commanster.eu/rcode.html>).
Maintained by Bruce Swihart. Last updated 2 years ago.
1 stars 8.35 score 358 scripts 70 dependents
brian-j-smith
MachineShop:Machine Learning Models and Tools
Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
Maintained by Brian J Smith. Last updated 7 months ago.
classification-modelsmachine-learningpredictive-modelingregression-modelssurvival-models
62 stars 7.95 score 121 scriptsbioc
sevenbridges:Seven Bridges Platform API Client and Common Workflow Language Tool Builder in R
R client and utilities for Seven Bridges platform API, from Cancer Genomics Cloud to other Seven Bridges supported platforms.
Maintained by Phil Webster. Last updated 5 months ago.
softwaredataimportthirdpartyclientapi-clientbioconductorbioinformaticscloudcommon-workflow-languagesevenbridges
35 stars 7.40 score 24 scripts
lcbc-uio
galamm:Generalized Additive Latent and Mixed Models
Estimates generalized additive latent and mixed models using maximum marginal likelihood, as defined in Sorensen et al. (2023) <doi:10.1007/s11336-023-09910-z>, which is an extension of Rabe-Hesketh and Skrondal (2004)'s unifying framework for multilevel latent variable modeling <doi:10.1007/BF02295939>. Efficient computation is done using sparse matrix methods, Laplace approximation, and automatic differentiation. The framework includes generalized multilevel models with heteroscedastic residuals, mixed response types, factor loadings, smoothing splines, crossed random effects, and combinations thereof. Syntax for model formulation is close to 'lme4' (Bates et al. (2015) <doi:10.18637/jss.v067.i01>) and 'PLmixed' (Rockwood and Jeon (2019) <doi:10.1080/00273171.2018.1516541>).
Maintained by Øystein Sørensen. Last updated 6 months ago.
generalized-additive-modelshierarchical-modelsitem-response-theorylatent-variable-modelsstructural-equation-modelscpp
29 stars 7.33 score 41 scripts
ambiorix-web
ambiorix:Web Framework Inspired by 'Express.js'
A web framework inspired by 'express.js' to build any web service from multi-page websites to 'RESTful' application programming interfaces.
Maintained by John Coene. Last updated 14 days ago.
212 stars 7.28 score 8 dependentsbioc
Xeva:Analysis of patient-derived xenograft (PDX) data
The Xeva package provides efficient and powerful functions for patient-drived xenograft (PDX) based pharmacogenomic data analysis. This package contains a set of functions to perform analysis of patient-derived xenograft data. This package was developed by the BHKLab, for further information please see our documentation.
Maintained by Benjamin Haibe-Kains. Last updated 9 days ago.
geneexpressionpharmacogeneticspharmacogenomicssoftwareclassification
11 stars 6.48 score 17 scripts
mayer79
flashlight:Shed Light on Black Box Machine Learning Models
Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <arXiv:1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (Gosiewska and Biecek (2019) <arxiv:1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.
Maintained by Michael Mayer. Last updated 8 months ago.
interpretabilityinterpretable-machine-learningmachine-learningxai
22 stars 6.25 score 54 scripts 1 dependents
capnrefsmmat
regressinator:Simulate and Diagnose (Generalized) Linear Models
Simulate samples from populations with known covariate distributions, generate response variables according to common linear and generalized linear model families, draw from sampling distributions of regression estimates, and perform visual inference on diagnostics from model fits.
Maintained by Alex Reinhart. Last updated 6 months ago.
4 stars 6.08 score 25 scripts
bupaverse
processcheckR:Rule-Based Conformance Checking of Business Process Event Data
Check compliance of event-data from (business) processes with respect to specified rules. Rules supported are of three types: frequency (activities that should (not) happen x number of times), order (succession between activities) and exclusiveness (and and exclusive choice between activities).
Maintained by Gert Janssenswillen. Last updated 2 years ago.
4 stars 5.58 score 32 scripts 1 dependents
mhahsler
arulesCBA:Classification Based on Association Rules
Provides the infrastructure for association rule-based classification including the algorithms CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM, RCAR, and RIPPER to build associative classifiers. Hahsler et al (2019) <doi:10.32614/RJ-2019-048>.
Maintained by Michael Hahsler. Last updated 7 months ago.
association-rulesclassification
3 stars 5.42 score 47 scripts 1 dependents
centerforstatistics-ugent
pim:Fit Probabilistic Index Models
Fit a probabilistic index model as described in Thas et al, 2012: <doi:10.1111/j.1467-9868.2011.01020.x>. The interface to the modeling function has changed in this new version. The old version is still available at R-Forge.
Maintained by Joris Meys. Last updated 3 months ago.
10 stars 5.33 score 43 scriptscenterforstatistics-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
cmmr
webqueue:Multicore HTTP Server
Distributes HTTP requests among a pool of background R processes. Supports timeouts and interrupts of requests to ensure that CPU cores are utilized effectively.
Maintained by Daniel P. Smith. Last updated 18 days ago.
2 stars 5.15 score
f-rousset
spaMM:Mixed-Effect Models, with or without Spatial Random Effects
Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.
Maintained by François Rousset. Last updated 10 months ago.
4.94 score 208 scripts 5 dependents
sciviews
mlearning:Machine Learning Algorithms with Unified Interface and Confusion Matrices
A unified interface is provided to various machine learning algorithms like linear or quadratic discriminant analysis, k-nearest neighbors, random forest, support vector machine, ... It allows to train, test, and apply cross-validation using similar functions and function arguments with a minimalist and clean, formula-based interface. Missing data are processed the same way as base and stats R functions for all algorithms, both in training and testing. Confusion matrices are also provided with a rich set of metrics calculated and a few specific plots.
Maintained by Philippe Grosjean. Last updated 2 years ago.
3.59 score 26 scripts 1 dependents
cran
ambiorix:Web Framework Inspired by 'Express.js'
A web framework inspired by 'express.js' to build any web service from multi-page websites to 'RESTful' application programming interfaces.
Maintained by John Coene. Last updated 14 days ago.
3.08 score 8 dependents
