Showing 40 of total 40 results (show query)
bertcarnell
lhs:Latin Hypercube Samples
Provides a number of methods for creating and augmenting Latin Hypercube Samples and Orthogonal Array Latin Hypercube Samples.
Maintained by Rob Carnell. Last updated 9 months ago.
latin-hypercubelatin-hypercube-samplelatin-hypercube-samplinglhsorthogonal-arrayscpp
71.9 match 44 stars 13.95 score 1.5k scripts 108 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 1 months ago.
arulesassociation-rulesfrequent-itemsets
6.3 match 194 stars 13.99 score 3.3k scripts 28 dependents
decisionpatterns
formula.tools:Programmatic Utilities for Manipulating Formulas, Expressions, Calls, Assignments and Other R Objects
These utilities facilitate the programmatic manipulations of formulas, expressions, calls, assignments and other R language objects. These objects all share the same structure: a left-hand side, operator and right-hand side. This packages provides methods for accessing and modifying this structures as well as extracting and replacing names and symbols from these objects.
Maintained by Christopher Brown. Last updated 7 years ago.
8.6 match 17 stars 8.89 score 236 scripts 79 dependents
spatstat
spatstat.utils:Utility Functions for 'spatstat'
Contains utility functions for the 'spatstat' family of packages which may also be useful for other purposes.
Maintained by Adrian Baddeley. Last updated 2 days ago.
spatial-analysisspatial-dataspatstat
4.5 match 5 stars 11.66 score 134 scripts 248 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.
3.3 match 93 stars 13.32 score 7.2k scripts 7 dependents
chelbert
DiceDesign:Designs of Computer Experiments
Space-Filling Designs and space-filling criteria (distance-based and uniformity-based), with emphasis to computer experiments; <doi:10.18637/jss.v065.i11>.
Maintained by Celine Helbert. Last updated 1 years ago.
6.5 match 6.12 score 231 scripts 64 dependents
bioc
snpStats:SnpMatrix and XSnpMatrix classes and methods
Classes and statistical methods for large SNP association studies. This extends the earlier snpMatrix package, allowing for uncertainty in genotypes.
Maintained by David Clayton. Last updated 5 months ago.
microarraysnpgeneticvariabilityzlib
4.0 match 9.41 score 674 scripts 17 dependents
temp20250212
MultiTraits:Analyzing and Visualizing Multidimensional Plant Traits
Implements analytical methods for multidimensional plant traits, including Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. Provides functions for data analysis, visualization, and network metrics calculation. Methods are based on Grime (1974) <doi:10.1038/250026a0>, Pierce et al. (2017) <doi:10.1111/1365-2435.12882>, Westoby (1998) <doi:10.1023/A:1004327224729>, Yang et al. (2022) <doi:10.1016/j.foreco.2022.120540>, Winemiller et al. (2015) <doi:10.1111/ele.12462>, He et al. (2020) <doi:10.1016/j.tree.2020.06.003>.
Maintained by Anonymous Author. Last updated 24 days ago.
8.2 match 3.90 score 16 scripts
ropensci
nlrx:Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via 'XML'
Setup, run and analyze 'NetLogo' (<https://ccl.northwestern.edu/netlogo/>) model simulations in 'R'. 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. The user defines all information that is needed in an intuitive framework, using class objects. Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. This also enables simulating 'NetLogo' experiments on remote high performance computing machines. In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.
Maintained by Sebastian Hanss. Last updated 6 months ago.
agent-based-modelingindividual-based-modellingnetlogopeer-reviewed
3.4 match 78 stars 8.86 score 195 scripts
hadley
lazyeval:Lazy (Non-Standard) Evaluation
An alternative approach to non-standard evaluation using formulas. Provides a full implementation of LISP style 'quasiquotation', making it easier to generate code with other code.
Maintained by Hadley Wickham. Last updated 3 years ago.
1.8 match 131 stars 15.74 score 520 scripts 1.8k dependents
statnet
ergm:Fit, Simulate and Diagnose Exponential-Family Models for Networks
An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i03> and Krivitsky, Hunter, Morris, and Klumb (2023) <doi:10.18637/jss.v105.i06>.
Maintained by Pavel N. Krivitsky. Last updated 7 days ago.
1.7 match 100 stars 15.36 score 1.4k scripts 36 dependents
rbgramacy
tgp:Bayesian Treed Gaussian Process Models
Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear models, CART, treed linear models, stationary separable and isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions (with projection and slice capabilities) and tree drawing, designed for visualization of tgp-class output. Sensitivity analysis and multi-resolution models are supported. Sequential experimental design and adaptive sampling functions are also provided, including ALM, ALC, and expected improvement. The latter supports derivative-free optimization of noisy black-box functions. For details and tutorials, see Gramacy (2007) <doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010) <doi:10.18637/jss.v033.i06>.
Maintained by Robert B. Gramacy. Last updated 6 months ago.
3.3 match 9 stars 7.36 score 203 scripts 12 dependentsprojectmosaic
mosaicCore:Common Utilities for Other MOSAIC-Family Packages
Common utilities used in other MOSAIC-family packages are collected here.
Maintained by Randall Pruim. Last updated 1 years ago.
3.3 match 1 stars 7.07 score 113 scripts 26 dependents
lrberge
fixest:Fast Fixed-Effects Estimations
Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://github.com/lrberge/fixest/blob/master/_DOCS/FENmlm_paper.pdf>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.
Maintained by Laurent Berge. Last updated 7 months ago.
1.5 match 387 stars 14.69 score 3.8k scripts 25 dependents
mlr-org
paradox:Define and Work with Parameter Spaces for Complex Algorithms
Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.
Maintained by Martin Binder. Last updated 8 months ago.
experimental-designhyperparametersmlr3transformations
1.8 match 29 stars 11.56 score 316 scripts 38 dependents
cran
mc2d:Tools for Two-Dimensional Monte-Carlo Simulations
A complete framework to build and study Two-Dimensional Monte-Carlo simulations, aka Second-Order Monte-Carlo simulations. Also includes various distributions (pert, triangular, Bernoulli, empirical discrete and continuous).
Maintained by Regis Pouillot. Last updated 9 months ago.
3.3 match 1 stars 6.28 score 16 dependents
nlmixr2
rxode2:Facilities for Simulating from ODE-Based Models
Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Maintained by Matthew L. Fidler. Last updated 1 months ago.
1.8 match 40 stars 11.24 score 220 scripts 13 dependents
jprybylski
xpose.xtras:Extra Functionality for the 'xpose' Package
Adding some at-present missing functionality, or functions unlikely to be added to the base 'xpose' package. This includes some diagnostic plots that have been missing in translation from 'xpose4', but also some useful features that truly extend the capabilities of what can be done with 'xpose'. These extensions include the concept of a set of 'xpose' objects, and diagnostics for likelihood-based models.
Maintained by John Prybylski. Last updated 4 months ago.
3.1 match 6.01 score 5 scripts
bcallaway11
BMisc:Miscellaneous Functions for Panel Data, Quantiles, and Printing Results
These are miscellaneous functions for working with panel data, quantiles, and printing results. For panel data, the package includes functions for making a panel data balanced (that is, dropping missing individuals that have missing observations in any time period), converting id numbers to row numbers, and to treat repeated cross sections as panel data under the assumption of rank invariance. For quantiles, there are functions to make distribution functions from a set of data points (this is particularly useful when a distribution function is created in several steps), to combine distribution functions based on some external weights, and to invert distribution functions. Finally, there are several other miscellaneous functions for obtaining weighted means, weighted distribution functions, and weighted quantiles; to generate summary statistics and their differences for two groups; and to add or drop covariates from formulas.
Maintained by Brantly Callaway. Last updated 1 months ago.
2.3 match 7 stars 7.92 score 110 scripts 8 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 2 months ago.
3.3 match 10 stars 5.33 score 43 scripts
ugroempi
DoE.wrapper:Wrapper Package for Design of Experiments Functionality
Various kinds of designs for (industrial) experiments can be created. The package uses, and sometimes enhances, design generation routines from other packages. So far, response surface designs from package 'rsm', Latin hypercube samples from packages 'lhs' and 'DiceDesign', and D-optimal designs from package 'AlgDesign' have been implemented.
Maintained by Ulrike Groemping. Last updated 2 years ago.
6.6 match 2.45 score 27 scripts 2 dependents
mathiasambuehl
cna:Causal Modeling with Coincidence Analysis
Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2018) <doi:10.1017/psrm.2018.45>. CNA is designed to recover INUS-causation from data, which is particularly relevant for analyzing processes featuring conjunctural causation (component causation) and equifinality (alternative causation). CNA is currently the only method for INUS-discovery that allows for multiple effects (outcomes/endogenous factors), meaning it can analyze common-cause and causal chain structures.
Maintained by Mathias Ambuehl. Last updated 8 months ago.
3.3 match 1 stars 4.78 score 45 scripts 3 dependents
shah-in-boots
rmdl:A Causality-Informed Modeling Approach
A system for describing and manipulating the many models that are generated in causal inference and data analysis projects, as based on the causal theory and criteria of Austin Bradford Hill (1965) <doi:10.1177/003591576505800503>. This system includes the addition of formal attributes that modify base `R` objects, including terms and formulas, with a focus on variable roles in the "do-calculus" of modeling, as described in Pearl (2010) <doi:10.2202/1557-4679.1203>. For example, the definition of exposure, outcome, and interaction are implicit in the roles variables take in a formula. These premises allow for a more fluent modeling approach focusing on variable relationships, and assessing effect modification, as described by VanderWeele and Robins (2007) <doi:10.1097/EDE.0b013e318127181b>. The essential goal is to help contextualize formulas and models in causality-oriented workflows.
Maintained by Anish S. Shah. Last updated 10 months ago.
epidemiologymodelingstatistics
3.3 match 4.60 score 7 scripts
bsaul
geex:An API for M-Estimation
Provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) <doi:10.1198/000313002753631330>). All examples from Stefanski & Boos (2002) are published in the corresponding Journal of Statistical Software paper "The Calculus of M-Estimation in R with geex" by Saul & Hudgens (2020) <doi:10.18637/jss.v092.i02>. Also provides an API to compute finite-sample variance corrections.
Maintained by Bradley Saul. Last updated 11 months ago.
asymptoticscovariance-estimatescovariance-estimationestimate-parametersestimating-equationsestimationinferencem-estimationrobustsandwich
1.8 match 8 stars 7.70 score 131 scripts 2 dependents
dipterix
dipsaus:A Dipping Sauce for Data Analysis and Visualizations
Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using the 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
Maintained by Zhengjia Wang. Last updated 6 days ago.
1.6 match 13 stars 7.90 score 85 scripts 3 dependentscran
arulesSequences:Mining Frequent Sequences
Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Maintained by Christian Buchta. Last updated 7 months ago.
3.3 match 12 stars 3.67 score 107 scripts
biooss
sensitivity:Global Sensitivity Analysis of Model Outputs and Importance Measures
A collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.
Maintained by Bertrand Iooss. Last updated 7 months ago.
1.7 match 17 stars 6.74 score 472 scripts 8 dependents
sfcheung
semfindr:Influential Cases in Structural Equation Modeling
Sensitivity analysis in structural equation modeling using influence measures and diagnostic plots. Support leave-one-out casewise sensitivity analysis presented by Pek and MacCallum (2011) <doi:10.1080/00273171.2011.561068> and approximate casewise influence using scores and casewise likelihood.
Maintained by Shu Fai Cheung. Last updated 14 days ago.
diagnosticsinfluential-caseslavaanoutlier-detectionsensitivity-analysisstructural-equation-modeling
1.8 match 1 stars 6.03 score 90 scripts
skranz
codeUtils:Helper functions for parsing and classifying R code. Useful for domain specific languages.
Very preliminary. May completely change
Maintained by Sebastian Kranz. Last updated 5 years ago.
4.3 match 2.16 score 12 scripts 4 dependents
antonio-pgarcia
rrepast:Invoke 'Repast Simphony' Simulation Models
An R and Repast integration tool for running individual-based (IbM) simulation models developed using 'Repast Simphony' Agent-Based framework directly from R code supporting multicore execution. This package integrates 'Repast Simphony' models within R environment, making easier the tasks of running and analyzing model output data for automated parameter calibration and for carrying out uncertainty and sensitivity analysis using the power of R environment.
Maintained by Antonio Prestes Garcia. Last updated 5 years ago.
1.9 match 3 stars 4.53 score 38 scripts 1 dependents
bristol-vaccine-centre
modelfitter:Bootstrapping models and model fits
This is a very early work in progress.
Maintained by Robert Challen. Last updated 11 months ago.
3.6 match 1 stars 2.00 scorebioc
combi:Compositional omics model based visual integration
This explorative ordination method combines quasi-likelihood estimation, compositional regression models and latent variable models for integrative visualization of several omics datasets. Both unconstrained and constrained integration are available. The results are shown as interpretable, compositional multiplots.
Maintained by Stijn Hawinkel. Last updated 5 months ago.
metagenomicsdimensionreductionmicrobiomevisualizationmetabolomics
1.6 match 1 stars 4.48 score 7 scriptsbioc
chopsticks:The 'snp.matrix' and 'X.snp.matrix' Classes
Implements classes and methods for large-scale SNP association studies
Maintained by Hin-Tak Leung. Last updated 3 months ago.
microarraysnpsandgeneticvariabilitysnpgeneticvariability
2.0 match 3.48 score 5 scripts
schoonees
vdg:Variance Dispersion Graphs and Fraction of Design Space Plots
Facilities for constructing variance dispersion graphs, fraction- of-design-space plots and similar graphics for exploring the properties of experimental designs. The design region is explored via random sampling, which allows for more flexibility than traditional variance dispersion graphs. A formula interface is leveraged to provide access to complex model formulae. Graphics can be constructed simultaneously for multiple experimental designs and/or multiple model formulae. Instead of using pointwise optimization to find the minimum and maximum scaled prediction variance curves, which can be inaccurate and time consuming, this package uses quantile regression as an alternative.
Maintained by Pieter Schoonees. Last updated 11 months ago.
3.3 match 2.00 score 10 scripts
till-tietz
parsel:Parallel Dynamic Web-Scraping Using 'RSelenium'
A system to increase the efficiency of dynamic web-scraping with 'RSelenium' by leveraging parallel processing. You provide a function wrapper for your 'RSelenium' scraping routine with a set of inputs, and 'parsel' runs it in several browser instances. Chunked input processing as well as error catching and logging ensures seamless execution and minimal data loss, even when unforeseen 'RSelenium' errors occur. You can additionally build safe scraping functions with minimal coding by utilizing constructor functions that act as wrappers around 'RSelenium' methods.
Maintained by Till Tietz. Last updated 1 years ago.
1.6 match 15 stars 3.88 score 8 scripts
sonjakuhnt
fanovaGraph:Building Kriging Models from FANOVA Graphs
Estimation and plotting of a function's FANOVA graph to identify the interaction structure and fitting, prediction and simulation of a Kriging model modified by the identified structure. The interactive function plotManipulate() can only be run on the 'RStudio IDE' with 'RStudio' package 'manipulate' loaded. 'RStudio' is freely available (<https://rstudio.com/>), and includes package 'manipulate'. The equivalent function plotTk() bases on CRAN Repository packages only. For further information on the method see Fruth, J., Roustant, O., Kuhnt, S. (2014) <doi:10.1016/j.jspi.2013.11.007>.
Maintained by Sonja Kuhnt. Last updated 4 years ago.
4.5 match 1 stars 1.20 score 16 scripts
collinerickson
sFFLHD:Sequential Full Factorial-Based Latin Hypercube Design
Gives design points from a sequential full factorial-based Latin hypercube design, as described in Duan, Ankenman, Sanchez, and Sanchez (2015, Technometrics, <doi:10.1080/00401706.2015.1108233>).
Maintained by Collin Erickson. Last updated 6 years ago.
2.0 match 2.70 score 6 scripts
ggrothendieck
gsubfn:Utilities for Strings and Function Arguments
The gsubfn function is like gsub but can take a replacement function or certain other objects instead of the replacement string. Matches and back references are input to the replacement function and replaced by the function output. gsubfn can be used to split strings based on content rather than delimiters and for quasi-perl-style string interpolation. The package also has facilities for translating formulas to functions and allowing such formulas in function calls instead of functions. This can be used with R functions such as apply, sapply, lapply, optim, integrate, xyplot, Filter and any other function that expects another function as an input argument or functions like cat or sql calls that may involve strings where substitution is desirable. There is also a facility for returning multiple objects from functions and a version of transform that allows the RHS to refer to LHS used in the same transform.
Maintained by G. Grothendieck. Last updated 7 years ago.
0.5 match 11 stars 10.58 score 872 scripts 76 dependentsugroempi
RcmdrPlugin.DoE:R Commander Plugin for (Industrial) Design of Experiments
Provides a platform-independent GUI for design of experiments. The package is implemented as a plugin to the R-Commander, which is a more general graphical user interface for statistics in R based on tcl/tk. DoE functionality can be accessed through the menu Design that is added to the R-Commander menus.
Maintained by Ulrike Groemping. Last updated 5 months ago.
2.3 match 3 stars 1.67 score 3 scripts