R-universe search: nsf

neotomadb

neotoma2:Working with the Neotoma Paleoecology Database

Access and manipulation of data using the Neotoma Paleoecology Database. <https://api.neotomadb.org/api-docs/>.

Maintained by Dominguez Vidana Socorro. Last updated 8 months ago.

earthcube neotoma nsf paleoecology

11.0 match 8 stars 5.35 score 56 scripts

ropensci

neotoma:Access to the Neotoma Paleoecological Database Through R

NOTE: This package is deprecated. Please use the neotoma2 package described at https://github.com/NeotomaDB/neotoma2. Access paleoecological datasets from the Neotoma Paleoecological Database using the published API (<http://wnapi.neotomadb.org/>), only containing datasets uploaded prior to June 2020. The functions in this package access various pre-built API functions and attempt to return the results from Neotoma in a usable format for researchers and the public.

Maintained by Simon J. Goring. Last updated 2 years ago.

neotoma neotoma-apis neotoma-database nsf paleoecology

11.0 match 30 stars 5.04 score 145 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-scholes differential-evolution genetic-algorithm grid-search heuristics implied-volatility local-search optimization particle-swarm-optimization simulated-annealing threshold-accepting

3.3 match 36 stars 9.56 score 101 scripts 4 dependents

cboettig

contentid:An Interface for Content-Based Identifiers

An interface for creating, registering, and resolving content-based identifiers for data management. Content-based identifiers rely on the 'cryptographic' hashes to refer to the files they identify, thus, anyone possessing the file can compute the identifier using a well-known standard algorithm, such as 'SHA256'. By registering a URL at which the content is accessible to a public archive (such as Hash Archive) or depositing data in a scientific repository such 'Zenodo', 'DataONE' or 'SoftwareHeritage', the content identifier can serve many functions typically associated with A Digital Object Identifier ('DOI'). Unlike location-based identifiers like 'DOIs', content-based identifiers permit the same content to be registered in many locations.

Maintained by Carl Boettiger. Last updated 2 months ago.

2.4 match 46 stars 7.59 score 108 scripts 3 dependents

dcgerard

segtest:Tests for Segregation Distortion in Polyploids

Provides a suite of tests for segregation distortion in F1 polyploid populations (for now, just tetraploids). This is under different assumptions of meiosis. Details of these methods are described in Gerard et al. (2025) <doi:10.1007/s00122-025-04816-z>. This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation.

Maintained by David Gerard. Last updated 2 months ago.

cpp

2.4 match 1 stars 4.85 score 3 scripts

dcgerard

hwep:Hardy-Weinberg Equilibrium in Polyploids

Inference concerning equilibrium and random mating in autopolyploids. Methods are available to test for equilibrium and random mating at any even ploidy level (>2) in the presence of double reduction at biallelic loci. For autopolyploid populations in equilibrium, methods are available to estimate the degree of double reduction. We also provide functions to calculate genotype frequencies at equilibrium, or after one or several rounds of random mating, given rates of double reduction. The main function is hwefit(). This material is based upon work supported by the National Science Foundation under Grant No. 2132247. The opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation. For details of these methods, see Gerard (2023a) <doi:10.1111/biom.13722> and Gerard (2023b) <doi:10.1111/1755-0998.13856>.

Maintained by David Gerard. Last updated 2 years ago.

cpp

2.4 match 3 stars 4.72 score 35 scripts

ropensci

awardFindR:awardFindR

Queries a number of scientific awards databases. Collects relevant results based on keyword and date parameters, returns list of projects that fit those criteria as a data frame. Sources include: Arnold Ventures, Carnegie Corp, Federal RePORTER, Gates Foundation, MacArthur Foundation, Mellon Foundation, NEH, NIH, NSF, Open Philanthropy, Open Society Foundations, Rockefeller Foundation, Russell Sage Foundation, Robert Wood Johnson Foundation, Sloan Foundation, Social Science Research Council, John Templeton Foundation, and USASpending.gov.

Maintained by Michael McCall. Last updated 12 months ago.

2.4 match 16 stars 4.38 score 3 scripts

gorelab

waves:Vis-NIR Spectral Analysis Wrapper

Originally designed application in the context of resource-limited plant research and breeding programs, 'waves' provides an open-source solution to spectral data processing and model development by bringing useful packages together into a streamlined pipeline. This package is wrapper for functions related to the analysis of point visible and near-infrared reflectance measurements. It includes visualization, filtering, aggregation, preprocessing, cross-validation set formation, model training, and prediction functions to enable open-source association of spectral and reference data. This package is documented in a peer-reviewed manuscript in the Plant Phenome Journal <doi:10.1002/ppj2.20012>. Specialized cross-validation schemes are described in detail in Jarquín et al. (2017) <doi:10.3835/plantgenome2016.12.0130>. Example data is from Ikeogu et al. (2017) <doi:10.1371/journal.pone.0188918>.

Maintained by Jenna Hershberger. Last updated 11 months ago.

1.6 match 6 stars 5.98 score 53 scripts

lter

lterpalettefinder:Extract Color Palettes from Photos and Pick Official LTER Palettes

Allows identification of palettes derived from LTER (Long Term Ecological Research) photographs based on user criteria. Also facilitates extraction of palettes from users' photos directly.

Maintained by Nicholas J Lyon. Last updated 2 years ago.

color-palette-generator data-science

1.5 match 27 stars 5.43 score 7 scripts

mhahsler

stream:Infrastructure for Data Stream Mining

A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.

Maintained by Michael Hahsler. Last updated 4 days ago.

data-stream-clustering datastream stream-mining cpp

0.8 match 39 stars 10.05 score 132 scripts 3 dependents

nceas

scicomptools:Tools Developed by the NCEAS Scientific Computing Support Team

Set of tools to import, summarize, wrangle, and visualize data. These functions were originally written based on the needs of the various synthesis working groups that were supported by the National Center for Ecological Analysis and Synthesis (NCEAS). These tools are meant to be useful inside and outside of the context for which they were designed.

Maintained by Angel Chen. Last updated 5 months ago.

data-science

1.5 match 9 stars 5.26 score 6 scripts

mikejohnson51

AHGestimation:An R package for Computing Robust, Mass Preserving Hydraulic Geometries and Rating Curves

Compute mass preserving 'At a station Hydraulic Geometry' (AHG) fits from river measurements.

Maintained by Mike Johnson. Last updated 3 months ago.

1.6 match 6 stars 5.02 score 10 scripts

lter

ltertools:Tools Developed by the Long Term Ecological Research Community

Set of the data science tools created by various members of the Long Term Ecological Research (LTER) community. These functions were initially written largely as standalone operations and have later been aggregated into this package.

Maintained by Nicholas Lyon. Last updated 23 days ago.

data-science lter-science

1.5 match 3 stars 4.95 score 4 scripts

cotterell

TDCM:The Transition Diagnostic Classification Model Framework

Estimate the transition diagnostic classification model (TDCM) described in Madison & Bradshaw (2018) <doi:10.1007/s11336-018-9638-5>, a longitudinal extension of the log-linear cognitive diagnosis model (LCDM) in Henson, Templin & Willse (2009) <doi:10.1007/s11336-008-9089-5>. As the LCDM subsumes many other diagnostic classification models (DCMs), many other DCMs can be estimated longitudinally via the TDCM. The 'TDCM' package includes functions to estimate the single-group and multigroup TDCM, summarize results of interest including item parameters, growth proportions, transition probabilities, transitional reliability, attribute correlations, model fit, and growth plots.

Maintained by Michael E. Cotterell. Last updated 4 months ago.

statistics

1.5 match 4.54 score 5 scripts

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.

0.5 match 93 stars 13.32 score 7.2k scripts 7 dependents

wmay

oc:Optimal Classification Roll Call Analysis Software

Estimates optimal classification (Poole 2000) <doi:10.1093/oxfordjournals.pan.a029814> scores from roll call votes supplied though a 'rollcall' object from package 'pscl'.

Maintained by William May. Last updated 2 years ago.

fortran ideal-points political-science openblas

1.5 match 2 stars 4.30 score 50 scripts

functionaldata

fdapace:Functional Data Analysis and Empirical Dynamics

A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.

Maintained by Yidong Zhou. Last updated 9 months ago.

cpp

0.5 match 31 stars 11.46 score 474 scripts 25 dependents

mikejohnson51

nwmTools:nwmTools

Tools for working with operational and historic National Water Model Output.

Maintained by Mike Johnson. Last updated 3 months ago.

conus noaa nwm streamflow

1.6 match 19 stars 3.06 score 12 scripts

projectmosaic

mosaicData:Project MOSAIC Data Sets

Data sets 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.

0.5 match 6 stars 8.33 score 632 scripts 8 dependents

cran

NPHazardRate:Nonparametric Hazard Rate Estimation

Provides functions and examples for histogram, kernel (classical, variable bandwidth and transformations based), discrete and semiparametric hazard rate estimators.

Maintained by Dimitrios Bagkavos. Last updated 6 years ago.

3.3 match 1.18 score 15 scripts

plfjohnson

adaptivetau:Tau-Leaping Stochastic Simulation

Implements adaptive tau leaping to approximate the trajectory of a continuous-time stochastic process as described by Cao et al. (2007) The Journal of Chemical Physics <doi:10.1063/1.2745299> (aka. the Gillespie stochastic simulation algorithm). This package is based upon work supported by NSF DBI-0906041 and NIH K99-GM104158 to Philip Johnson and NIH R01-AI049334 to Rustom Antia.

Maintained by Philip Johnson. Last updated 5 months ago.

openblas cpp

0.5 match 7.23 score 138 scripts 2 dependents

ericgiunta

Colossus:"Risk Model Regression and Analysis with Complex Non-Linear Models"

Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards <https://en.wikipedia.org/wiki/Proportional_hazards_model>, Poisson <https://en.wikipedia.org/wiki/Poisson_regression>, and Fine-Gray competing risks <https://www.publichealth.columbia.edu/research/population-health-methods/competing-risk-analysis> regression are supported. This work was sponsored by NASA Grant 80NSSC19M0161 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.

Maintained by Eric Giunta. Last updated 3 days ago.

cpp openmp

0.5 match 1 stars 7.06 score 36 scripts

mjlajeunesse

metagear:Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis

Functionalities for facilitating systematic reviews, data extractions, and meta-analyses. It includes a GUI (graphical user interface) to help screen the abstracts and titles of bibliographic data; tools to assign screening effort across multiple collaborators/reviewers and to assess inter- reviewer reliability; tools to help automate the download and retrieval of journal PDF articles from online databases; figure and image extractions from PDFs; web scraping of citations; automated and manual data extraction from scatter-plot and bar-plot images; PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagrams; simple imputation tools to fill gaps in incomplete or missing study parameters; generation of random effects sizes for Hedges' d, log response ratio, odds ratio, and correlation coefficients for Monte Carlo experiments; covariance equations for modelling dependencies among multiple effect sizes (e.g., effect sizes with a common control); and finally summaries that replicate analyses and outputs from widely used but no longer updated meta-analysis software (i.e., metawin). Funding for this package was supported by National Science Foundation (NSF) grants DBI-1262545 and DEB-1451031. CITE: Lajeunesse, M.J. (2016) Facilitating systematic reviews, data extraction and meta-analysis with the metagear package for R. Methods in Ecology and Evolution 7, 323-330 <doi:10.1111/2041-210X.12472>.

Maintained by Marc J. Lajeunesse. Last updated 4 years ago.

0.5 match 14 stars 6.71 score 91 scripts

dcgerard

tensr:Covariance Inference and Decompositions for Tensor Datasets

A collection of functions for Kronecker structured covariance estimation and testing under the array normal model. For estimation, maximum likelihood and Bayesian equivariant estimation procedures are implemented. For testing, a likelihood ratio testing procedure is available. This package also contains additional functions for manipulating and decomposing tensor data sets. This work was partially supported by NSF grant DMS-1505136. Details of the methods are described in Gerard and Hoff (2015) <doi:10.1016/j.jmva.2015.01.020> and Gerard and Hoff (2016) <doi:10.1016/j.laa.2016.04.033>.

Maintained by David Gerard. Last updated 2 years ago.

0.5 match 5 stars 6.53 score 56 scripts 4 dependents

laurabruckman

netSEM:Network Structural Equation Modeling

The network structural equation modeling conducts a network statistical analysis on a data frame of coincident observations of multiple continuous variables [1]. It builds a pathway model by exploring a pool of domain knowledge guided candidate statistical relationships between each of the variable pairs, selecting the 'best fit' on the basis of a specific criteria such as adjusted r-squared value. This material is based upon work supported by the U.S. National Science Foundation Award EEC-2052776 and EEC-2052662 for the MDS-Rely IUCRC Center, under the NSF Solicitation: NSF 20-570 Industry-University Cooperative Research Centers Program [1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013) <doi:10.1109/ACCESS.2013.2267611>.

Maintained by Laura S. Bruckman. Last updated 2 years ago.

0.8 match 3.72 score 13 scripts

mhahsler

rEMM:Extensible Markov Model for Modelling Temporal Relationships Between Clusters

Implements TRACDS (Temporal Relationships between Clusters for Data Streams), a generalization of Extensible Markov Model (EMM). TRACDS adds a temporal or order model to data stream clustering by superimposing a dynamically adapting Markov Chain. Also provides an implementation of EMM (TRACDS on top of tNN data stream clustering). Development of this package was supported in part by NSF IIS-0948893 and R21HG005912 from the National Human Genome Research Institute. Hahsler and Dunham (2010) <doi:10.18637/jss.v035.i05>.

Maintained by Michael Hahsler. Last updated 7 months ago.

clustering data-stream sequence-analysis

0.5 match 2 stars 4.79 score 31 scripts

gloewing

sMTL:Sparse Multi-Task Learning

Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.

Maintained by Gabriel Loewinger. Last updated 2 years ago.

1.5 match 1.00 score 8 scripts

jmniehaus

bizicount:Bivariate Zero-Inflated Count Models Using Copulas

Maximum likelihood estimation of copula-based zero-inflated (and non-inflated) Poisson and negative binomial count models, based on the article <doi:10.18637/jss.v109.i01>. Supports Frank and Gaussian copulas. Allows for mixed margins (e.g., one margin Poisson, the other zero-inflated negative binomial), and several marginal link functions. Built-in methods for publication-quality tables using 'texreg', post-estimation diagnostics using 'DHARMa', and testing for marginal zero-modification via <doi:10.1177/0962280217749991>. For information on copula regression for count data, see Genest and Nešlehová (2007) <doi:10.1017/S0515036100014963> as well as Nikoloulopoulos (2013) <doi:10.1007/978-3-642-35407-6_11>. For information on zero-inflated count regression generally, see Lambert (1992) <https://www.jstor.org/stable/1269547?origin=crossref>. The author acknowledges support by NSF DMS-1925119 and DMS-212324.

Maintained by John Niehaus. Last updated 11 months ago.

0.5 match 2 stars 3.00 score 8 scripts

tianxili

randnet:Random Network Model Estimation, Selection and Parameter Tuning

Model selection and parameter tuning procedures for a class of random network models. The model selection can be done by a general cross-validation framework called ECV from Li et. al. (2016) <arXiv:1612.04717> . Several other model-based and task-specific methods are also included, such as NCV from Chen and Lei (2016) <arXiv:1411.1715>, likelihood ratio method from Wang and Bickel (2015) <arXiv:1502.02069>, spectral methods from Le and Levina (2015) <arXiv:1507.00827>. Many network analysis methods are also implemented, such as the regularized spectral clustering (Amini et. al. 2013 <doi:10.1214/13-AOS1138>) and its degree corrected version and graphon neighborhood smoothing (Zhang et. al. 2015 <arXiv:1509.08588>). It also includes the consensus clustering of Gao et. al. (2014) <arXiv:1410.5837>, the method of moments estimation of nomination SBM of Li et. al. (2020) <arxiv:2008.03652>, and the network mixing method of Li and Le (2021) <arxiv:2106.02803>. It also includes the informative core-periphery data processing method of Miao and Li (2021) <arXiv:2101.06388>. The work to build and improve this package is partially supported by the NSF grants DMS-2015298 and DMS-2015134.

Maintained by Tianxi Li. Last updated 2 years ago.

0.5 match 2.45 score 47 scripts 2 dependents

vroshanjoseph

MOFAT:Maximum One-Factor-at-a-Time Designs

Identifying important factors from a large number of potentially important factors of a highly nonlinear and computationally expensive black box model is a difficult problem. Xiao, Joseph, and Ray (2022) <doi:10.1080/00401706.2022.2141897> proposed Maximum One-Factor-at-a-Time (MOFAT) designs for doing this. A MOFAT design can be viewed as an improvement to the random one-factor-at-a-time (OFAT) design proposed by Morris (1991) <doi:10.1080/00401706.1991.10484804>. The improvement is achieved by exploiting the connection between Morris screening designs and Monte Carlo-based Sobol' designs, and optimizing the design using a space-filling criterion. This work is supported by a U.S. National Science Foundation (NSF) grant CMMI-1921646 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921646>.

Maintained by V. Roshan Joseph. Last updated 2 years ago.

0.8 match 1.00 score

yili-hong

SPREDA:Statistical Package for Reliability Data Analysis

The Statistical Package for REliability Data Analysis (SPREDA) implements recently-developed statistical methods for the analysis of reliability data. Modern technological developments, such as sensors and smart chips, allow us to dynamically track product/system usage as well as other environmental variables, such as temperature and humidity. We refer to these variables as dynamic covariates. The package contains functions for the analysis of time-to-event data with dynamic covariates and degradation data with dynamic covariates. The package also contains functions that can be used for analyzing time-to-event data with right censoring, and with left truncation and right censoring. Financial support from NSF and DuPont are acknowledged.

Maintained by Yili Hong. Last updated 6 years ago.

0.5 match 1.43 score 27 scripts

kolassa-dev

MultNonParam:Multivariate Nonparametric Methods

A collection of multivariate nonparametric methods, selected in part to support an MS level course in nonparametric statistical methods. Methods include adjustments for multiple comparisons, implementation of multivariate Mann-Whitney-Wilcoxon testing, inversion of these tests to produce a confidence region, some permutation tests for linear models, and some algorithms for calculating exact probabilities associated with one- and two- stage testing involving Mann-Whitney-Wilcoxon statistics. Supported by grant NSF DMS 1712839. See Kolassa and Seifu (2013) <doi:10.1016/j.acra.2013.03.006>.

Maintained by John E. Kolassa. Last updated 2 years ago.

fortran openblas

0.5 match 1.18 score 15 scripts

kolassa-dev

PHInfiniteEstimates:Tools for Inference in the Presence of a Monotone Likelihood

Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents. Supported by grant NSF DMS 1712839.

Maintained by John E. Kolassa. Last updated 1 years ago.

0.5 match 1.00 score

cran

twingp:A Fast Global-Local Gaussian Process Approximation

A global-local approximation framework for large-scale Gaussian process modeling. Please see Vakayil and Joseph (2024) <doi:10.1080/00401706.2023.2296451> for details. This work is supported by U.S. NSF grants CMMI-1921646 and DMREF-1921873.

Maintained by Akhil Vakayil. Last updated 6 months ago.

cpp openmp

0.5 match 1.00 score

cran

supercompress:Supervised Compression of Big Data

A supervised compression method that incorporates the response for reducing big data to a carefully selected subset. Please see Joseph and Mak (2021) <doi:10.1002/sam.11508>. This research is supported by a U.S. National Science Foundation (NSF) grant CMMI-1921646.

Maintained by Chaofan Huang. Last updated 3 years ago.

0.5 match 1 stars 1.00 score