Showing 111 of total 111 results (show query)
thomasp85
particles:A Graph Based Particle Simulator Based on D3-Force
Simulating particle movement in 2D space has many application. The 'particles' package implements a particle simulator based on the ideas behind the 'd3-force' 'JavaScript' library. 'particles' implements all forces defined in 'd3-force' as well as others such as vector fields, traps, and attractors.
Maintained by Thomas Lin Pedersen. Last updated 3 months ago.
d3jsgraph-layoutnetworknetwork-visualizationparticlessimulationcpp
108.8 match 119 stars 7.19 score 43 scripts
kingaa
pomp:Statistical Inference for Partially Observed Markov Processes
Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
Maintained by Aaron A. King. Last updated 1 months ago.
abcb-splinedifferential-equationsdynamical-systemsiterated-filteringlikelihoodlikelihood-freemarkov-chain-monte-carlomarkov-modelmathematical-modellingmeasurement-errorparticle-filtersequential-monte-carlosimulation-based-inferencesobol-sequencestate-spacestatistical-inferencestochastic-processestime-seriesopenblas
15.3 match 115 stars 11.81 score 1.3k scripts 4 dependents
bioc
flowcatchR:Tools to analyze in vivo microscopy imaging data focused on tracking flowing blood cells
flowcatchR is a set of tools to analyze in vivo microscopy imaging data, focused on tracking flowing blood cells. It guides the steps from segmentation to calculation of features, filtering out particles not of interest, providing also a set of utilities to help checking the quality of the performed operations (e.g. how good the segmentation was). It allows investigating the issue of tracking flowing cells such as in blood vessels, to categorize the particles in flowing, rolling and adherent. This classification is applied in the study of phenomena such as hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is delivered alongside the package, and can enable fully reproducible bioimage analysis in the R environment.
Maintained by Federico Marini. Last updated 3 months ago.
softwarevisualizationcellbiologyclassificationinfrastructureguishinyappsbioconductorfluorescencemicroscopyparticlestracking
29.7 match 4 stars 5.62 score 8 scripts
enricoschumann
NMOF:Numerical Methods and Optimization in Finance
Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Maintained by Enrico Schumann. Last updated 30 days ago.
black-scholesdifferential-evolutiongenetic-algorithmgrid-searchheuristicsimplied-volatilitylocal-searchoptimizationparticle-swarm-optimizationsimulated-annealingthreshold-accepting
12.0 match 36 stars 9.56 score 101 scripts 4 dependents
brunettheo
particle.swarm.optimisation:Optimisation with Particle Swarm Optimisation
A toolbox to create a particle swarm optimisation (PSO), the package contains two classes: the Particle and the Particle Swarm, this two class is used to run the PSO with methods to easily print, plot and save the result.
Maintained by Theo Brunet. Last updated 4 years ago.
44.9 match 2.48 score 6 scripts 1 dependents
mooresm
serrsBayes:Bayesian Modelling of Raman Spectroscopy
Sequential Monte Carlo (SMC) algorithms for fitting a generalised additive mixed model (GAMM) to surface-enhanced resonance Raman spectroscopy (SERRS), using the method of Moores et al. (2016) <arXiv:1604.07299>. Multivariate observations of SERRS are highly collinear and lend themselves to a reduced-rank representation. The GAMM separates the SERRS signal into three components: a sequence of Lorentzian, Gaussian, or pseudo-Voigt peaks; a smoothly-varying baseline; and additive white noise. The parameters of each component of the model are estimated iteratively using SMC. The posterior distributions of the parameters given the observed spectra are represented as a population of weighted particles.
Maintained by Matt Moores. Last updated 4 years ago.
bayesianchemometricsramansequential-monte-carlospectroscopycpp
16.9 match 8 stars 5.46 score 36 scripts
stewid
SimInf:A Framework for Data-Driven Stochastic Disease Spread Simulations
Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>. The package also provides functionality to fit models to time series data using the Approximate Bayesian Computation Sequential Monte Carlo ('ABC-SMC') algorithm of Toni and others (2009) <doi:10.1098/rsif.2008.0172>.
Maintained by Stefan Widgren. Last updated 5 days ago.
data-drivenepidemiologyhigh-performance-computingmarkov-chainmathematical-modellinggslopenmp
9.1 match 35 stars 10.09 score 227 scripts
helske
bssm:Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
Efficient methods for Bayesian inference of state space models via Markov chain Monte Carlo (MCMC) based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>), particle MCMC, and its delayed acceptance version. Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with linear-Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported. See Helske and Vihola (2021, <doi:10.32614/RJ-2021-103>) for details.
Maintained by Jouni Helske. Last updated 6 months ago.
bayesian-inferencecppmarkov-chain-monte-carloparticle-filterstate-spacetime-seriesopenblascppopenmp
13.8 match 42 stars 6.43 score 11 scripts
julienmoeys
soiltexture:Functions for Soil Texture Plot, Classification and Transformation
"The Soil Texture Wizard" is a set of R functions designed to produce texture triangles (also called texture plots, texture diagrams, texture ternary plots), classify and transform soil textures data. These functions virtually allows to plot any soil texture triangle (classification) into any triangle geometry (isosceles, right-angled triangles, etc.). This set of function is expected to be useful to people using soil textures data from different soil texture classification or different particle size systems. Many (> 15) texture triangles from all around the world are predefined in the package. A simple text based graphical user interface is provided: soiltexture_gui().
Maintained by Julien Moeys. Last updated 1 years ago.
12.2 match 28 stars 7.11 score 136 scripts 1 dependents
emilopezcano
SixSigma:Six Sigma Tools for Quality Control and Improvement
Functions and utilities to perform Statistical Analyses in the Six Sigma way. Through the DMAIC cycle (Define, Measure, Analyze, Improve, Control), you can manage several Quality Management studies: Gage R&R, Capability Analysis, Control Charts, Loss Function Analysis, etc. Data frames used in the books "Six Sigma with R" [ISBN 978-1-4614-3652-2] and "Quality Control with R" [ISBN 978-3-319-24046-6], are also included in the package.
Maintained by Emilio L. Cano. Last updated 2 years ago.
quality-controlquality-improvementsix-sigmaspc
10.9 match 15 stars 7.82 score 169 scripts 1 dependents
mrc-ide
mcstate:Monte Carlo Methods for State Space Models
Implements Monte Carlo methods for state-space models such as 'SIR' models in epidemiology. Particle MCMC (pmcmc) and SMC2 methods are planned. This package is particularly designed to work with odin/dust models, but we will see how general it becomes.
Maintained by Rich FitzJohn. Last updated 9 months ago.
11.8 match 19 stars 7.08 score 87 scripts
rcppsmc
RcppSMC:Rcpp Bindings for Sequential Monte Carlo
R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.
Maintained by Dirk Eddelbuettel. Last updated 2 months ago.
particle-filterrcppsequantial-monte-carloopenblascpp
14.5 match 25 stars 5.35 score 7 scripts
markhogue
AeroSampleR:Estimate Aerosol Particle Collection Through Sample Lines
Estimate ideal efficiencies of aerosol sampling through sample lines. Functions were developed consistent with the approach described in Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), "Hand Calculations for Transport of Radioactive Aerosols through Sampling Systems" Health Phys 106, 5, S78-S87, <doi:10.1097/HP.0000000000000092>.
Maintained by Mark Hogue. Last updated 2 years ago.
18.0 match 3.70 score 2 scripts
ncss-tech
aqp:Algorithms for Quantitative Pedology
The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Maintained by Dylan Beaudette. Last updated 29 days ago.
digital-soil-mappingncss-technrcspedologypedometricssoilsoil-surveyusda
5.1 match 55 stars 11.77 score 1.2k scripts 2 dependents
marjoleinbruijning
trackdem:Particle Tracking and Demography
Obtain population density and body size structure, using video material or image sequences as input. Functions assist in the creation of image sequences from videos, background detection and subtraction, particle identification and tracking. An artificial neural network can be trained for noise filtering. The goal is to supply accurate estimates of population size, structure and/or individual behavior, for use in evolutionary and ecological studies.
Maintained by Marjolein Bruijning. Last updated 3 years ago.
12.0 match 10 stars 4.88 score 15 scripts
eldarrak
FLightR:Reconstruct Animal Paths from Solar Geolocation Loggers Data
Spatio-temporal locations of an animal are computed from annotated data with a hidden Markov model via particle filter algorithm. The package is relatively robust to varying degrees of shading. The hidden Markov model is described in Movement Ecology - Rakhimberdiev et al. (2015) <doi:10.1186/s40462-015-0062-5>, general package description is in the Methods in Ecology and Evolution - Rakhimberdiev et al. (2017) <doi:10.1111/2041-210X.12765> and package accuracy assessed in the Journal of Avian Biology - Rakhimberdiev et al. (2016) <doi:10.1111/jav.00891>.
Maintained by Eldar Rakhimberdiev. Last updated 6 months ago.
movement-ecologysolar-geolocation-loggerssolar-geolocator
7.4 match 22 stars 7.26 score 111 scripts
richardgeveritt
ggsmc:Visualising Output from Sequential Monte Carlo and Ensemble-Based Methods
Functions for plotting, and animating, the output of importance samplers, sequential Monte Carlo samplers (SMC) and ensemble-based methods. The package can be used to plot and animate histograms, densities, scatter plots and time series, and to plot the genealogy of an SMC or ensemble-based algorithm. These functions all rely on algorithm output to be supplied in tidy format. A function is provided to transform algorithm output from matrix format (one Monte Carlo point per row) to the tidy format required by the plotting and animating functions.
Maintained by Richard G Everitt. Last updated 2 months ago.
10.1 match 4.48 score 6 scripts
jonathanlees
RSEIS:Seismic Time Series Analysis Tools
Multiple interactive codes to view and analyze seismic data, via spectrum analysis, wavelet transforms, particle motion, hodograms. Includes general time-series tools, plotting, filtering, interactive display.
Maintained by Jonathan M. Lees. Last updated 6 months ago.
10.0 match 3 stars 4.27 score 262 scripts 4 dependents
cran
pso:Particle Swarm Optimization
Provides an implementation of particle swarm optimisation consistent with the standard PSO 2007/2011 by Maurice Clerc. Additionally a number of ancillary routines are provided for easy testing and graphics.
Maintained by Claus Bendtsen. Last updated 3 years ago.
9.6 match 4 stars 4.22 score 23 dependents
uncertaintyquantification
FastGaSP:Fast and Exact Computation of Gaussian Stochastic Process
Implements fast and exact computation of Gaussian stochastic process with the Matern kernel using forward filtering and backward smoothing algorithm. It includes efficient implementations of the inverse Kalman filter, with applications such as estimating particle interaction functions. These tools support models with or without noise. Additionally, the package offers algorithms for fast parameter estimation in latent factor models, where the factor loading matrix is orthogonal, and latent processes are modeled by Gaussian processes. See the references: 1) Mengyang Gu and Yanxun Xu (2020), Journal of Computational and Graphical Statistics; 2) Xinyi Fang and Mengyang Gu (2024), <doi:10.48550/arXiv.2407.10089>; 3) Mengyang Gu and Weining Shen (2020), Journal of Machine Learning Research; 4) Yizi Lin, Xubo Liu, Paul Segall and Mengyang Gu (2025), <doi:10.48550/arXiv.2501.01324>.
Maintained by Mengyang Gu. Last updated 1 months ago.
18.2 match 2.18 score 25 scripts 1 dependents
rbgramacy
plgp:Particle Learning of Gaussian Processes
Sequential Monte Carlo (SMC) inference for fully Bayesian Gaussian process (GP) regression and classification models by particle learning (PL) following Gramacy & Polson (2011) <arXiv:0909.5262>. The sequential nature of inference and the active learning (AL) hooks provided facilitate thrifty sequential design (by entropy) and optimization (by improvement) for classification and regression models, respectively. This package essentially provides a generic PL interface, and functions (arguments to the interface) which implement the GP models and AL heuristics. Functions for a special, linked, regression/classification GP model and an integrated expected conditional improvement (IECI) statistic provide for optimization in the presence of unknown constraints. Separable and isotropic Gaussian, and single-index correlation functions are supported. See the examples section of ?plgp and demo(package="plgp") for an index of demos.
Maintained by Robert B. Gramacy. Last updated 2 years ago.
13.3 match 1 stars 2.96 score 102 scripts 3 dependents
arsilva87
soilphysics:Soil Physical Analysis
Basic and model-based soil physical analyses.
Maintained by Anderson Rodrigo da Silva. Last updated 3 years ago.
8.1 match 11 stars 4.82 score 12 scripts
nimble-dev
nimble:MCMC, Particle Filtering, and Programmable Hierarchical Modeling
A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, Laplace Approximation, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.
Maintained by Christopher Paciorek. Last updated 4 days ago.
bayesian-inferencebayesian-methodshierarchical-modelsmcmcprobabilistic-programmingopenblascpp
2.9 match 169 stars 12.97 score 2.6k scripts 19 dependentsbioc
TrIdent:TrIdent - Transduction Identification
The `TrIdent` R package automates the analysis of transductomics data by detecting, classifying, and characterizing read coverage patterns associated with potential transduction events. Transductomics is a DNA sequencing-based method for the detection and characterization of transduction events in pure cultures and complex communities. Transductomics relies on mapping sequencing reads from a viral-like particle (VLP)-fraction of a sample to contigs assembled from the metagenome (whole-community) of the same sample. Reads from bacterial DNA carried by VLPs will map back to the bacterial contigs of origin creating read coverage patterns indicative of ongoing transduction.
Maintained by Jessie Maier. Last updated 13 days ago.
coveragemetagenomicspatternlogicclassificationsequencingbacteriophagehorizontal-gene-transferpattern-matchingphagesequencing-coveragetransductiontransductomicsvirus-like-particle
7.2 match 2 stars 5.04 score 7 scripts
konrad1991
paropt:Parameter Optimizing of ODE-Systems
Enable optimization of parameters of ordinary differential equations. Therefore, using 'SUNDIALS' to solve the ODE-System (see Hindmarsh, Alan C., Peter N. Brown, Keith E. Grant, Steven L. Lee, Radu Serban, Dan E. Shumaker, and Carol S. Woodward. (2005) <doi:10.1145/1089014.1089020>). Furthermore, for optimization the particle swarm algorithm is used (see: Akman, Devin, Olcay Akman, and Elsa Schaefer. (2018) <doi:10.1155/2018/9160793> and Sengupta, Saptarshi, Sanchita Basak, and Richard Peters. (2018) <doi:10.3390/make1010010>).
Maintained by Krämer Konrad. Last updated 9 months ago.
optimizationparoptparticle-swarm-optimizationrcpprcpparmadillocpp
8.4 match 3 stars 4.26 score 12 scriptsmrc-ide
dust2:Next Generation dust
Experimental sources for the next generation of dust, which will properly adopt the particle filter, have support for partial parameter updates, support for multiple parameter sets and hopefully better GPU/MPI support.
Maintained by Rich FitzJohn. Last updated 10 days ago.
5.4 match 6.66 score 32 scripts 2 dependents
statmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
7.0 match 5 stars 4.94 score 544 scriptsnimble-dev
nimbleSMC:Sequential Monte Carlo Methods for 'nimble'
Includes five particle filtering algorithms for use with state space models in the 'nimble' system: 'Auxiliary', 'Bootstrap', 'Ensemble Kalman filter', 'Iterated Filtering 2', and 'Liu-West', as described in Michaud et al. (2021), <doi:10.18637/jss.v100.i03>. A full User Manual is available at <https://r-nimble.org>.
Maintained by Christopher Paciorek. Last updated 2 months ago.
7.4 match 2 stars 4.62 score 35 scripts
iandryden
shapes:Statistical Shape Analysis
Routines for the statistical analysis of landmark shapes, including Procrustes analysis, graphical displays, principal components analysis, permutation and bootstrap tests, thin-plate spline transformation grids and comparing covariance matrices. See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, with Applications in R (2nd Edition), John Wiley and Sons.
Maintained by Ian Dryden. Last updated 4 months ago.
3.8 match 7 stars 8.50 score 225 scripts 24 dependents
nano-optics
terms:T-matrix for Electromagnetic Radiation with Multiple Scatterers
A set of Fortran modules/routines for T-matrix-based calculations of light scattering by clusters of individual scatterers.
Maintained by Baptiste Auguié. Last updated 7 months ago.
4.8 match 7 stars 6.46 score 828 scriptscran
boot:Bootstrap Functions (Originally by Angelo Canty for S)
Functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.
Maintained by Alessandra R. Brazzale. Last updated 7 months ago.
3.8 match 2 stars 8.21 score 2.3k dependents
leef-uzh
bemovi.LEEF:BEMOVI, software for extracting BEhaviour and MOrphology from VIdeos. This version is adapted for LEEF-UZH
An R and ImageJ based work flow to automatically measure behaviour and morphology from videos. Moving individuals are identified by background subtraction, morphology extracted, and trajectories assembled through time from coordinate data. Abundance, morphology and behaviour can be summarized based on trajectory data.
Maintained by Rainer M Krug. Last updated 1 years ago.
9.1 match 3.32 score 2 dependents
troyhill
coreCT:Programmatic Analysis of Sediment Cores Using Computed Tomography Imaging
Computed tomography (CT) imaging is a powerful tool for understanding the composition of sediment cores. This package streamlines and accelerates the analysis of CT data generated in the context of environmental science. Included are tools for processing raw DICOM images to characterize sediment composition (sand, peat, etc.). Root analyses are also enabled, including measures of external surface area and volumes for user-defined root size classes. For a detailed description of the application of computed tomography imaging for sediment characterization, see: Davey, E., C. Wigand, R. Johnson, K. Sundberg, J. Morris, and C. Roman. (2011) <DOI: 10.1890/10-2037.1>.
Maintained by Troy D. Hill. Last updated 4 years ago.
biomasscomputed-tomographysedimentsediment-core
6.6 match 3 stars 4.41 score 17 scripts
tianshu129
foqat:Field Observation Quick Analysis Toolkit
Tools for quickly processing and analyzing field observation data and air quality data. This tools contain functions that facilitate analysis in atmospheric chemistry (especially in ozone pollution). Some functions of time series are also applicable to other fields. For detail please view homepage<https://github.com/tianshu129/foqat>. Scientific Reference: 1. The Hydroxyl Radical (OH) Reactivity: Roger Atkinson and Janet Arey (2003) <doi:10.1021/cr0206420>. 2. Ozone Formation Potential (OFP): <https://ww2.arb.ca.gov/sites/default/files/classic/regact/2009/mir2009/mir10.pdf>, Zhang et al.(2021) <doi:10.5194/acp-21-11053-2021>. 3. Aerosol Formation Potential (AFP): Wenjing Wu et al. (2016) <doi:10.1016/j.jes.2016.03.025>. 4. TUV model: <https://www2.acom.ucar.edu/modeling/tropospheric-ultraviolet-and-visible-tuv-radiation-model>.
Maintained by Tianshu Chen. Last updated 6 months ago.
air-pollutionair-qualityair-quality-dataair-quality-measurementsair-quality-monitorair-quality-reportsair-quality-sensoratmospheric-chemistryatmospheric-modellingatmospheric-sciencedaily-maximum-8-hour-ozonefield-observationmirofpozone-formation-potentialphotolysis-rate-coefficientstime-seriestime-series-analysistuv
6.3 match 35 stars 4.54 score 20 scripts
jeremyroos
gmgm:Gaussian Mixture Graphical Model Learning and Inference
Gaussian mixture graphical models include Bayesian networks and dynamic Bayesian networks (their temporal extension) whose local probability distributions are described by Gaussian mixture models. They are powerful tools for graphically and quantitatively representing nonlinear dependencies between continuous variables. This package provides a complete framework to create, manipulate, learn the structure and the parameters, and perform inference in these models. Most of the algorithms are described in the PhD thesis of Roos (2018) <https://tel.archives-ouvertes.fr/tel-01943718>.
Maintained by Jérémy Roos. Last updated 3 years ago.
bayesian-networksgaussian-mixture-modelsinferencemachine-learningprobabilistic-graphical-models
8.4 match 5 stars 3.40 score 7 scripts
spatpomp-org
spatPomp:Inference for Spatiotemporal Partially Observed Markov Processes
Inference on panel data using spatiotemporal partially-observed Markov process (SpatPOMP) models. The 'spatPomp' package extends 'pomp' to include algorithms taking advantage of the spatial structure in order to assist with handling high dimensional processes. See Asfaw et al. (2024) <doi:10.48550/arXiv.2101.01157> for further description of the package.
Maintained by Edward Ionides. Last updated 4 months ago.
3.7 match 2 stars 7.38 score 93 scripts
sbfnk
rbi.helpers:'rbi' Helper Functions
Contains a collection of helper functions to use with 'rbi', the R interface to 'LibBi', described in Murray et al. (2015) <doi:10.18637/jss.v067.i10>. It contains functions to adapt the proposal distribution and number of particles in particle Markov-Chain Monte Carlo, as well as calculating the Deviance Information Criterion (DIC) and converting between times in 'LibBi' results and R time/dates.
Maintained by Sebastian Funk. Last updated 2 years ago.
4.1 match 4 stars 6.48 score 380 scriptsmrc-ide
dust:Iterate Multiple Realisations of Stochastic Models
An Engine for simulation of stochastic models. Includes support for running stochastic models in parallel, either with shared or varying parameters. Simulations are run efficiently in compiled code and can be run with a fraction of simulated states returned to R, allowing control over memory usage. Support is provided for building bootstrap particle filter for performing Sequential Monte Carlo (e.g., Gordon et al. 1993 <doi:10.1049/ip-f-2.1993.0015>). The core of the simulation engine is the 'xoshiro256**' algorithm (Blackman and Vigna <arXiv:1805.01407>), and the package is further described in FitzJohn et al 2021 <doi:10.12688/wellcomeopenres.16466.2>.
Maintained by Rich FitzJohn. Last updated 6 months ago.
3.3 match 18 stars 7.84 score 60 scripts 3 dependents
wincowgerdev
OpenSpecy:Analyze, Process, Identify, and Share Raman and (FT)IR Spectra
Raman and (FT)IR spectral analysis tool for plastic particles and other environmental samples (Cowger et al. 2021, <doi:10.1021/acs.analchem.1c00123>). With read_any(), Open Specy provides a single function for reading individual, batch, or map spectral data files like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies processing spectra, including smoothing, baseline correction, range restriction and flattening, intensity conversions, wavenumber alignment, and min-max normalization. Spectra can be identified in batch using an onboard reference library (Cowger et al. 2020, <doi:10.1177/0003702820929064>) using match_spec(). A Shiny app is available via run_app() or online at <https://openanalysis.org/openspecy/>.
Maintained by Win Cowger. Last updated 17 days ago.
3.3 match 29 stars 7.58 score 22 scripts
zsteinmetz
envalysis:Miscellaneous Functions for Environmental Analyses
Small toolbox for data analyses in environmental chemistry and ecotoxicology. Provides, for example, calibration() to calculate calibration curves and corresponding limits of detection (LODs) and limits of quantification (LOQs) according to German DIN 32645 (2008). texture() makes it easy to estimate soil particle size distributions from hydrometer measurements (ASTM D422-63, 2007).
Maintained by Zacharias Steinmetz. Last updated 5 months ago.
analyticschemistryecotoxicologyenvironmentsoil
3.8 match 8 stars 6.30 score 83 scripts
mingstat
ZIM:Zero-Inflated Models (ZIM) for Count Time Series with Excess Zeros
Analyze count time series with excess zeros. Two types of statistical models are supported: Markov regression by Yang et al. (2013) <doi:10.1016/j.stamet.2013.02.001> and state-space models by Yang et al. (2015) <doi:10.1177/1471082X14535530>. They are also known as observation-driven and parameter-driven models respectively in the time series literature. The functions used for Markov regression or observation-driven models can also be used to fit ordinary regression models with independent data under the zero-inflated Poisson (ZIP) or zero-inflated negative binomial (ZINB) assumption. Besides, the package contains some miscellaneous functions to compute density, distribution, quantile, and generate random numbers from ZIP and ZINB distributions.
Maintained by Ming Yang. Last updated 1 years ago.
4.0 match 8 stars 5.95 score 32 scripts
cneyens
raem:Analytic Element Modeling of Steady Single-Layer Groundwater Flow
A model of single-layer groundwater flow in steady-state under the Dupuit-Forchheimer assumption can be created by placing elements such as wells, area-sinks and line-sinks at arbitrary locations in the flow field. Output variables include hydraulic head and the discharge vector. Particle traces can be computed numerically in three dimensions. The underlying theory is described in Haitjema (1995) <doi:10.1016/B978-0-12-316550-3.X5000-4> and references therein.
Maintained by Cas Neyens. Last updated 7 months ago.
analytic-element-modelgroundwatergroundwater-modellinghydrogeologyhydrology
4.0 match 8 stars 5.81 score 6 scripts
karlines
OceanView:Visualisation of Oceanographic Data and Model Output
Functions for transforming and viewing 2-D and 3-D (oceanographic) data and model output.
Maintained by Karline Soetaert. Last updated 1 years ago.
5.6 match 4.08 score 60 scripts
florianhartig
BayesianTools:General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics
General-purpose MCMC and SMC samplers, as well as plots and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.
Maintained by Florian Hartig. Last updated 1 years ago.
bayesecological-modelsmcmcoptimizationsmcsystems-biologycpp
2.2 match 122 stars 10.17 score 580 scripts 5 dependents
kcf-jackson
animate:A Web-Based Graphics Device for Animated Visualisations
Implements a web-based graphics device for animated visualisations. Modelled on the 'base' syntax, it extends the 'base' graphics functions to support frame-by-frame animation and keyframes animation. The target use cases are real-time animated visualisations, including agent-based models, dynamical systems, and animated diagrams. The generated visualisations can be deployed as GIF images / MP4 videos, as 'Shiny' apps (with interactivity) or as HTML documents through embedding into R Markdown documents.
Maintained by Chun Fung Kwok. Last updated 11 months ago.
2.8 match 30 stars 6.88 score 84 scripts
f0nzie
rODE:Ordinary Differential Equation (ODE) Solvers Written in R Using S4 Classes
Show physics, math and engineering students how an ODE solver is made and how effective R classes can be for the construction of the equations that describe natural phenomena. Inspiration for this work comes from the book on "Computer Simulations in Physics" by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. Book link: <http://www.compadre.org/osp/items/detail.cfm?ID=7375>.
Maintained by Alfonso R. Reyes. Last updated 7 years ago.
3.3 match 5.50 score 71 scriptscran
trend:Non-Parametric Trend Tests and Change-Point Detection
The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
Maintained by Thorsten Pohlert. Last updated 1 years ago.
3.4 match 3 stars 5.31 score 9 dependents
university-of-newcastle-research
pmwg:Particle Metropolis Within Gibbs
Provides an R implementation of the Particle Metropolis within Gibbs sampler for model parameter, covariance matrix and random effect estimation. A more general implementation of the sampler based on the paper by Gunawan, D., Hawkins, G. E., Tran, M. N., Kohn, R., & Brown, S. D. (2020) <doi:10.1016/j.jmp.2020.102368>. An HTML tutorial document describing the package is available at <https://university-of-newcastle-research.github.io/samplerDoc/> and includes several detailed examples, some background and troubleshooting steps.
Maintained by Gavin Cooper. Last updated 1 years ago.
3.6 match 3 stars 4.94 score 29 scripts
tpetzoldt
simecol:Simulation of Ecological (and Other) Dynamic Systems
An object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. It supports structuring of simulation scenarios (to avoid copy and paste) and aims to improve readability and re-usability of code.
Maintained by Thomas Petzoldt. Last updated 7 months ago.
3.6 match 4.76 score 190 scripts
crlsierra
SoilR:Models of Soil Organic Matter Decomposition
Functions for modeling Soil Organic Matter decomposition in terrestrial ecosystems with linear and nonlinear systems of differential equations. The package implements models according to the compartmental system representation described in Sierra and others (2012) <doi:10.5194/gmd-5-1045-2012> and Sierra and others (2014) <doi:10.5194/gmd-7-1919-2014>.
Maintained by Carlos A. Sierra. Last updated 1 years ago.
5.7 match 5 stars 2.88 score 153 scripts
ropensci
tidyhydat:Extract and Tidy Canadian 'Hydrometric' Data
Provides functions to access historical and real-time national 'hydrometric' data from Water Survey of Canada data sources (<https://dd.weather.gc.ca/hydrometric/csv/> and <https://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>) and then applies tidy data principles.
Maintained by Sam Albers. Last updated 5 days ago.
citzgovernment-datahydrologyhydrometricstidy-datawater-resources
1.7 match 71 stars 9.59 score 202 scripts 3 dependentsmrc-ide
odin2:Next generation odin
Temporary package for rewriting odin.
Maintained by Rich FitzJohn. Last updated 2 months ago.
2.5 match 5 stars 6.32 score 22 scripts
chrisscod
LMfilteR:Filter Methods for Parameter Estimation in Linear and Non Linear Regression Models
We present a method based on filtering algorithms to estimate the parameters of linear, i.e. the coefficients and the variance of the error term. The proposed algorithms make use of Particle Filters following Ristic, B., Arulampalam, S., Gordon, N. (2004, ISBN: 158053631X) resampling methods. Parameters of logistic regression models are also estimated using an evolutionary particle filter method.
Maintained by Christian Llano Robayo. Last updated 2 years ago.
7.5 match 1 stars 2.00 score 2 scriptsnano-optics
mie:Mie scattering
Numerical implementation of Mie scattering theory for light scattering by spherical particles.
Maintained by Baptiste Auguie. Last updated 2 years ago.
3.5 match 8 stars 4.26 score 15 scripts
computationalstylistics
stylo:Stylometric Multivariate Analyses
Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.
Maintained by Maciej Eder. Last updated 2 months ago.
1.7 match 187 stars 8.58 score 462 scripts
jeswheel
panelPomp:Inference for Panel Partially Observed Markov Processes
Data analysis based on panel partially-observed Markov process (PanelPOMP) models. To implement such models, simulate them and fit them to panel data, 'panelPomp' extends some of the facilities provided for time series data by the 'pomp' package. Implemented methods include filtering (panel particle filtering) and maximum likelihood estimation (Panel Iterated Filtering) as proposed in Breto, Ionides and King (2020) "Panel Data Analysis via Mechanistic Models" <doi:10.1080/01621459.2019.1604367>.
Maintained by Jesse Wheeler. Last updated 3 months ago.
2.4 match 5.91 score 45 scripts
biooss
mistral:Methods in Structural Reliability
Various reliability analysis methods for rare event inference (computing failure probability and quantile from model/function outputs).
Maintained by Bertrand Iooss. Last updated 1 years ago.
5.8 match 1 stars 2.43 score 27 scripts
manuhuth
coconots:Convolution-Closed Models for Count Time Series
Useful tools for fitting, validating, and forecasting of practical convolution-closed time series models for low counts are provided. Marginal distributions of the data can be modelled via Poisson and Generalized Poisson innovations. Regression effects can be incorprated through time varying innovation rates. The models are described in Jung and Tremayne (2011) <doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x> and, Tsay (1992) <doi:10.2307/2347612>.
Maintained by Manuel Huth. Last updated 1 months ago.
3.3 match 3 stars 4.18 score 4 scripts
tbrown122387
pfr:Interface to the 'C++' Library 'Pf'
Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs. Algorithms include the Bootstrap Filter from Gordon et al. (1993) <doi:10.1049/ip-f-2.1993.0015>, the generic SISR filter, the Auxiliary Particle Filter from Pitt et al (1999) <doi:10.2307/2670179>, and a variety of Rao-Blackwellized particle filters inspired by Andrieu et al. (2002) <doi:10.1111/1467-9868.00363>. For more details on the 'c++' library 'pf', see Brown (2020) <doi:10.21105/joss.02599>.
Maintained by Taylor Brown. Last updated 1 years ago.
5.1 match 2.70 score 3 scriptscran
TSSS:Time Series Analysis with State Space Model
Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (2020, ISBN: 978-0-367-18733-0).
Maintained by Masami Saga. Last updated 1 years ago.
7.3 match 2 stars 1.78 score
weecology
LDATS:Latent Dirichlet Allocation Coupled with Time Series Analyses
Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial time series methods in a two-stage analysis to quantify dynamics in high-dimensional temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, whose relative proportions are modeled using generalized Bayesian time series models that include abrupt changepoints and smooth dynamics. The methods are described in Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>, Western and Kleykamp (2004) <doi:10.1093/pan/mph023>, Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) <doi:10.1002/ecy.2373>.
Maintained by Juniper L. Simonis. Last updated 5 years ago.
changepointldaparallel-temperingportalsoftmax
1.9 match 25 stars 6.93 score 45 scriptsuncertaintyquantification
AIUQ:Ab Initio Uncertainty Quantification
Uncertainty quantification and inverse estimation by probabilistic generative models from the beginning of the data analysis. An example is a Fourier basis method for inverse estimation in scattering analysis of microscopy videos. It does not require specifying a certain range of Fourier bases and it substantially reduces computational cost via the generalized Schur algorithm. See the reference: Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), <doi:10.48550/arXiv.2309.02468>.
Maintained by Mengyang Gu. Last updated 9 months ago.
5.5 match 2.30 score 1 scriptscran
pmhtutorial:Minimal Working Examples for Particle Metropolis-Hastings
Routines for state estimate in a linear Gaussian state space model and a simple stochastic volatility model using particle filtering. Parameter inference is also carried out in these models using the particle Metropolis-Hastings algorithm that includes the particle filter to provided an unbiased estimator of the likelihood. This package is a collection of minimal working examples of these algorithms and is only meant for educational use and as a start for learning to them on your own.
Maintained by Johan Dahlin. Last updated 6 years ago.
12.2 match 1.00 scoremrc-ide
monty:Monte Carlo Models
Experimental sources for the next generation of mcstate, now called 'monty', which will support much of the old mcstate functionality but new things like better parameter interfaces, Hamiltonian Monte Carlo, and other features.
Maintained by Rich FitzJohn. Last updated 1 months ago.
1.5 match 3 stars 7.52 score 29 scripts 3 dependents
europeanifcbgroup
iRfcb:Tools for Managing Imaging FlowCytobot (IFCB) Data
A comprehensive suite of tools for managing, processing, and analyzing data from the IFCB. I R FlowCytobot ('iRfcb') supports quality control, geospatial analysis, and preparation of IFCB data for publication in databases like <https://www.gbif.org>, <https://www.obis.org>, <https://emodnet.ec.europa.eu/en>, <https://shark.smhi.se/>, and <https://www.ecotaxa.org>. The package integrates with the MATLAB 'ifcb-analysis' tool, which is described in Sosik and Olson (2007) <doi:10.4319/lom.2007.5.204>, and provides features for working with raw, manually classified, and machine learning–classified image datasets. Key functionalities include image extraction, particle size distribution analysis, taxonomic data handling, and biomass concentration calculations, essential for plankton research.
Maintained by Anders Torstensson. Last updated 11 hours ago.
1.8 match 1 stars 5.72 scorecran
airGR:Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Hydrological modelling tools developed at INRAE-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR5H, GR4J, GR5J, GR6J, GR2M, GR1A) that can be applied either on a lumped or semi-distributed way. A snow accumulation and melt model (CemaNeige) and the associated functions for the calibration and evaluation of models are also included. Use help(airGR) for package description and references.
Maintained by Olivier Delaigue. Last updated 1 years ago.
1.5 match 4 stars 6.60 score 164 scripts 4 dependentsbioc
cyanoFilter:Phytoplankton Population Identification using Cell Pigmentation and/or Complexity
An approach to filter out and/or identify phytoplankton cells from all particles measured via flow cytometry pigment and cell complexity information. It does this using a sequence of one-dimensional gates on pre-defined channels measuring certain pigmentation and complexity. The package is especially tuned for cyanobacteria, but will work fine for phytoplankton communities where there is at least one cell characteristic that differentiates every phytoplankton in the community.
Maintained by Oluwafemi Olusoji. Last updated 5 months ago.
flowcytometryclusteringonechannel
2.2 match 4.30 score 4 scripts
nano-optics
cda:Coupled-Dipole Approximation for Electromagnetic Scattering by Three- Dimensional Clusters of Sub-Wavelength Particles
Coupled-dipole simulations for electromagnetic scattering of light by sub-wavelength particles in arbitrary 3-dimensional configurations. Scattering and absorption spectra are simulated by inversion of the interaction matrix, or by an order-of-scattering approximation scheme. High-level functions are provided to simulate spectra with varying angles of incidence, as well as with full angular averaging.
Maintained by Baptiste Auguie. Last updated 3 years ago.
3.2 match 2 stars 2.78 score 60 scripts
levimcclenny
BoolFilter:Optimal Estimation of Partially Observed Boolean Dynamical Systems
Tools for optimal and approximate state estimation as well as network inference of Partially-Observed Boolean Dynamical Systems.
Maintained by Levi McClenny. Last updated 7 years ago.
2.3 match 3.70 score 10 scripts
coffeemuggler
eseis:Environmental Seismology Toolbox
Environmental seismology is a scientific field that studies the seismic signals, emitted by Earth surface processes. This package provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history.
Maintained by Michael Dietze. Last updated 4 months ago.
1.9 match 9 stars 4.42 score 58 scripts
bogdanpotanin
gena:Genetic Algorithm and Particle Swarm Optimization
Implements genetic algorithm and particle swarm algorithm for real-valued functions. Various modifications (including hybridization and elitism) of these algorithms are provided. Implemented functions are based on ideas described in S. Katoch, S. Chauhan, V. Kumar (2020) <doi:10.1007/s11042-020-10139-6> and M. Clerc (2012) <https://hal.archives-ouvertes.fr/hal-00764996>.
Maintained by Bogdan Potanin. Last updated 3 years ago.
5.5 match 1.48 score 1 dependents
tjmckinley
SimBIID:Simulation-Based Inference Methods for Infectious Disease Models
Provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>). Also provides functions to plot and summarise the outputs.
Maintained by Trevelyan J. McKinley. Last updated 3 years ago.
2.7 match 2 stars 3.00 score 4 scripts
mechantrouquin
RCALI:Calculation of the Integrated Flow of Particles Between Polygons
Calculate the flow of particles between polygons by two integration methods: integration by a cubature method and integration on a grid of points. Annie Bouvier, Kien Kieu, Kasia Adamczyk and Herve Monod (2009) <doi:10.1016/j.envsoft.2008.11.006>.
Maintained by Jean-Francois Rey. Last updated 5 months ago.
7.1 match 1.08 score 12 scripts
omori-yasuhiro
ASV:Stochastic Volatility Models with or without Leverage
The efficient Markov chain Monte Carlo estimation of stochastic volatility models with and without leverage (asymmetric and symmetric stochastic volatility models). Further, it computes the logarithm of the likelihood given parameters using particle filters.
Maintained by Yasuhiro Omori. Last updated 1 years ago.
7.4 match 1.00 score 1 scripts
asgr
snapshot:Gadget N-body cosmological simulation code snapshot format 1 and 2 I/O utilities
Functions for reading and writing Gadget N-body format 1 and 2 snapshots. The Gadget code is popular in astronomy for running N-body / hydrodynamical cosmological and merger simulations. To find out more about Gadget see the main distribution page at www.mpa-garching.mpg.de/gadget/. Format 1 specific functions end with a ".1" suffix and format 2 specific functions end with a ".2" suffix. Generic functions have neither suffix.
Maintained by Aaron Robotham. Last updated 4 years ago.
3.5 match 1 stars 2.00 score 7 scripts
roliveros-ramos
ibm:Individual Based Models in R
Implementation of some (simple) Individual Based Models and methods to create new ones, particularly for population dynamics models (reproduction, mortality and movement). The basic operations for the simulations are implemented in Rcpp for speed.
Maintained by Ricardo Oliveros-Ramos. Last updated 1 years ago.
1.9 match 1 stars 3.61 score 27 scriptscran
NPCirc:Nonparametric Circular Methods
Nonparametric smoothing methods for density and regression estimation involving circular data, including the estimation of the mean regression function and other conditional characteristics.
Maintained by Maria Alonso-Pena. Last updated 2 years ago.
3.8 match 1.78 score 2 dependents
firefly-cpp
niarules:Numerical Association Rule Mining using Population-Based Nature-Inspired Algorithms
Framework is devoted to mining numerical association rules through the utilization of nature-inspired algorithms for optimization. Drawing inspiration from the 'NiaARM' 'Python' and the 'NiaARM' 'Julia' packages, this repository introduces the capability to perform numerical association rule mining in the R programming language. Fister Jr., Iglesias, Galvez, Del Ser, Osaba and Fister (2018) <doi:10.1007/978-3-030-03493-1_9>.
Maintained by Iztok Jr. Fister. Last updated 12 days ago.
association-rulesmetaheuristicsoptimization
1.7 match 1 stars 3.70 score 2 scriptscran
psoptim:Particle Swarm Optimization
Particle swarm optimization - a basic variant.
Maintained by Krzysztof Ciupke. Last updated 9 years ago.
5.9 match 1.00 scorecran
radar:Fundamental Formulas for Radar
Fundamental formulas for Radar, for attenuation, range, velocity, effectiveness, power, scatter, doppler, geometry, radar equations, etc. Based on Nick Guy's Python package PyRadarMet
Maintained by Jose Gama. Last updated 10 years ago.
5.6 match 1 stars 1.00 scoreleef-uzh
LEEF.measurement.bemovi:Prepares Movies for Analysis with Bemovi and Extracts Data
Module for the LEEF pipeline to process bemovi data.
Maintained by Rainer M. Krug. Last updated 3 years ago.
3.7 match 1.48 score 1 dependents
whzsdhr
LHD:Latin Hypercube Designs (LHDs)
Contains different algorithms and construction methods for optimal Latin hypercube designs (LHDs) with flexible sizes. Our package is comprehensive since it is capable of generating maximin distance LHDs, maximum projection LHDs, and orthogonal and nearly orthogonal LHDs. Detailed comparisons and summary of all the algorithms and construction methods in this package can be found at Hongzhi Wang, Qian Xiao and Abhyuday Mandal (2021) <doi:10.48550/arXiv.2010.09154>. This package is particularly useful in the area of Design and Analysis of Experiments (DAE). More specifically, design of computer experiments.
Maintained by Hongzhi Wang. Last updated 1 months ago.
1.9 match 1 stars 2.30 score 6 scripts
cran
SoilFDA:Fractal Dimension Analysis of Soil Particle Size Distribution
Function for the computation of fractal dimension based on mass of soil particle size distribution by Tyler & Wheatcraft (1992) <doi:10.2136/sssaj1992.03615995005600020005x>. It also provides functions for calculation of mean weight and geometric mean diameter of particle size distribution by Perfect et al. (1992) <doi:10.2136/sssaj1992.03615995005600050012x>.
Maintained by Fehim Jeelani Wani. Last updated 10 months ago.
3.6 match 1.00 score
bmlmcmc
naspaclust:Nature-Inspired Spatial Clustering
Implement and enhance the performance of spatial fuzzy clustering using Fuzzy Geographically Weighted Clustering with various optimization algorithms, mainly from Xin She Yang (2014) <ISBN:9780124167438> with book entitled Nature-Inspired Optimization Algorithms. The optimization algorithm is useful to tackle the disadvantages of clustering inconsistency when using the traditional approach. The distance measurements option is also provided in order to increase the quality of clustering results. The Fuzzy Geographically Weighted Clustering with nature inspired optimisation algorithm was firstly developed by Arie Wahyu Wijayanto and Ayu Purwarianti (2014) <doi:10.1109/CITSM.2014.7042178> using Artificial Bee Colony algorithm.
Maintained by Bahrul Ilmi Nasution. Last updated 4 years ago.
1.7 match 2.00 score
calbertsen
caMisc:Different Functions
More about what it does (maybe more than one line)
Maintained by Christoffer Moesgaard Albertsen. Last updated 9 months ago.
2.0 match 1.70 score
solmonta
ratios:Calculating Ratios Between Two Data Sets and Correction for Adhering Particles on Plants
Calculation of ratios between two data sets containing environmental data like element concentrations by different methods. Additionally plant element concentrations can be corrected for adhering particles (soil, airborne dust).
Maintained by Solveig Pospiech. Last updated 7 years ago.
3.3 match 1.00 score 3 scriptsrbgramacy
dynaTree:Dynamic Trees for Learning and Design
Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential design and optimization, fully online learning with drift, variable selection, and sensitivity analysis of inputs. Illustrative examples from the original dynamic trees paper (Gramacy, Taddy & Polson (2011); <doi:10.1198/jasa.2011.ap09769>) are facilitated by demos in the package; see demo(package="dynaTree").
Maintained by Robert B. Gramacy. Last updated 7 months ago.
1.9 match 2 stars 1.66 score 23 scripts
certara-jcraig
Certara.RDarwin:Interface for 'pyDarwin' Machine Learning Pharmacometric Model Development
Utilities that support the usage of 'pyDarwin' (<https://certara.github.io/pyDarwin/>) for ease of setup and execution of a machine learning based pharmacometric model search with Certara's Non-Linear Mixed Effects (NLME) modeling engine.
Maintained by James Craig. Last updated 19 days ago.
1.7 match 1.70 score
aboulaboul
automl:Deep Learning with Metaheuristic
Fits from simple regression to highly customizable deep neural networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.
Maintained by Alex Boulangé. Last updated 5 years ago.
0.5 match 28 stars 5.61 score 29 scripts
mattocci27
LeafArea:Rapid Digital Image Analysis of Leaf Area
An interface for the image processing program 'ImageJ', which allows a rapid digital image analysis for particle sizes. This package includes function to write an 'ImageJ' macro which is optimized for a leaf area analysis by default.
Maintained by Masatoshi Katabuchi. Last updated 2 years ago.
0.5 match 36 stars 4.84 score 19 scripts
sam-data-guy-iam
animalEKF:Extended Kalman Filters for Animal Movement
Synthetic generation of 1-D and 2-D correlated random walks (CRWs) for animal movement with behavioral switching, and particle filter estimation of movement parameters from observed trajectories using Extended Kalman Filter (EKF) model. See Ackerman (2018) <https://digital.library.temple.edu/digital/collection/p245801coll10/id/499150>.
Maintained by Samuel Ackerman. Last updated 1 years ago.
2.3 match 1 stars 1.00 score
antonio-pgarcia
evoper:Evolutionary Parameter Estimation for 'Repast Simphony' Models
The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible package providing optimization driven parameter estimation methods using metaheuristics and evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require, in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there are built in support for models developed with 'Repast Simphony' Agent-Based framework (<https://repast.github.io/>) and with NetLogo (<https://ccl.northwestern.edu/netlogo/>) which are the most used frameworks for Agent-based modeling.
Maintained by Antonio Prestes Garcia. Last updated 5 years ago.
0.5 match 6 stars 3.92 score 28 scripts
obreschkow
nbody:Gravitational N-Body Simulation
Run simple direct gravitational N-body simulations. The package can access different external N-body simulators (e.g. GADGET-4 by Springel et al. (2021) <doi:10.48550/arXiv.2010.03567>), but also has a simple built-in simulator. This default simulator uses a variable block time step and lets the user choose between a range of integrators, including 4th and 6th order integrators for high-accuracy simulations. Basic top-hat smoothing is available as an option. The code also allows the definition of background particles that are fixed or in uniform motion, not subject to acceleration by other particles.
Maintained by Danail Obreschkow. Last updated 5 months ago.
0.8 match 2.48 score 1 scriptscran
EnviroPRA2:Environmental Probabilistic Risk Assessment Tools
It contains functions for dose calculation for different routes, fitting data to probability distributions, random number generation (Monte Carlo simulation) and calculation of systemic and carcinogenic risks. For more information see the publication: Barrio-Parra et al. (2019) "Human-health probabilistic risk assessment: the role of exposure factors in an urban garden scenario" <doi:10.1016/j.landurbplan.2019.02.005>.
Maintained by Fernando Barrio-Parra. Last updated 1 years ago.
1.9 match 1.00 score
cran
airGRdatassim:Ensemble-Based Data Assimilation with GR Hydrological Models
Add-on to the 'airGR' package which provides the tools to assimilate observed discharges in daily GR hydrological models. The package consists in two functions allowing to perform the assimilation of observed discharges via the Ensemble Kalman filter or the Particle filter as described in Piazzi et al. (2021) <doi:10.1029/2020WR028390>.
Maintained by Olivier Delaigue. Last updated 4 years ago.
0.5 match 2 stars 3.00 score
oteros
AeRobiology:A Computational Tool for Aerobiological Data
Different tools for managing databases of airborne particles, elaborating the main calculations and visualization of results. In a first step, data are checked using tools for quality control and all missing gaps are completed. Then, the main parameters of the pollen season are calculated and represented graphically. Multiple graphical tools are available: pollen calendars, phenological plots, time series, tendencies, interactive plots, abundance plots...
Maintained by "Jose Oteros". Last updated 6 years ago.
0.5 match 1 stars 2.46 score 29 scripts
insileco
refR:An R package to get and manage BibTeX/YAML/JSON references
The package \textbf{refR} retrieves author references from Scopus Search and Crossref APIs and returns references as BibTeX files (function \code{\link[refR]{getRefs}}). It also allows to convert BibTeX files in more readable formats (i.e. YAML and JSON) by calling the software pandoc-citeproc (functions \code{\link[refR]{getRefs}} and \code{\link[refR]{bib2yaml}}). Information in references files can be cleaned using the function \code{\link[refR]{cleanRefs}}. This function translates special characters (accented characters and other LaTeX tags) and also cleans author names (detection of particle in family names, removal of uppercase except for each first letter of family and given names, and shorten given name).
Maintained by Nicolas Casajus. Last updated 6 years ago.
0.5 match 5 stars 2.40 score 2 scriptshelske
particlefield:Sequential Monte Carlo for Latent Conditional Autoregressive Model
Functions for replicating the results of the latent Gaussian Markov random field experiment of Lindsten, Helske, Vihola (2018), XX. Contains also functions for performing particle Markov chain Monte Carlo estimation of the model parameters.
Maintained by Jouni Helske. Last updated 4 years ago.
0.5 match 3 stars 2.18 score 4 scriptscran
sievetest:Laboratory Sieve Test Reporting Functions
Functions for making particle-size analysis. Sieve tests are widely used to obtain particle-size distribution of powders or granular materials.
Maintained by Petr Matousu. Last updated 7 years ago.
0.8 match 1.00 score
agandy
chopthin:The Chopthin Resampler
Resampling is a standard step in particle filtering and in sequential Monte Carlo. This package implements the chopthin resampler, which keeps a bound on the ratio between the largest and the smallest weights after resampling.
Maintained by Axel Gandy. Last updated 7 years ago.
0.5 match 1.00 score 3 scriptscran
RZigZag:Zig-Zag Sampler
Implements the Zig-Zag algorithm (Bierkens, Fearnhead, Roberts, 2016) <arXiv:1607.03188> applied and Bouncy Particle Sampler <arXiv:1510.02451> for a Gaussian target and Student distribution.
Maintained by Joris Bierkens. Last updated 6 years ago.
0.5 match 1.00 score 5 scripts
ajakef
rTephra:Tephra Transport Modeling
Models and displays tephra transport through custom (windy, turbulent, heterogeneous) atmosphere over custom topography. Includes a Lagrangian (particle-tracking) tephra transport model and a function to save snapshots of model as png files.
Maintained by Jake Anderson. Last updated 6 years ago.
0.5 match 1.00 score 6 scripts
ranjitstat
PWEV:PSO Based Weighted Ensemble Algorithm for Volatility Modelling
Price volatility refers to the degree of variation in series over a certain period of time. This volatility is especially noticeable in agricultural commodities, adding uncertainty for farmers, traders, and others in the agricultural supply chain. Commonly and popularly used four volatility models viz, GARCH, Glosten Jagannatan Runkle-GARCH (GJR-GARCH) model, exponentially weighted moving average (EWMA) model and Multiplicative Error Model (MEM) are selected and implemented. PWAVE, weighted ensemble model based on particle swarm optimization (PSO) is proposed to combine the forecast obtained from all the candidate models. This package has been developed using algorithm of Paul et al. <doi:10.1007/s40009-023-01218-x> and Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.
Maintained by Dr. Ranjit Kumar Paul. Last updated 11 months ago.
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