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r-fgac
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public |
Bi-variate data fitting is done by two stochastic components: the marginal distributions and the dependency structure. The dependency structure is modeled through a copula. An algorithm was implemented considering seven families of copulas (Generalized Archimedean Copulas), the best fitting can be obtained looking all copula's options (totally positive of order 2 and stochastically increasing models).
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2025-04-22 |
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r-ffmetadata
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public |
A collection of functions that allows users to retrieve metadata for the Fragile Families challenge via a Web API (<http://api.metadata.fragilefamilies.princeton.edu>). Users can select and search metadata for relevant variables by filtering on different attribute names.
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2025-04-22 |
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r-ffmanova
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public |
General linear modeling with multiple responses (MANCOVA). An overall p-value for each model term is calculated by the 50-50 MANOVA method by Langsrud (2002) <doi:10.1111/1467-9884.00320>, which handles collinear responses. Rotation testing, described by Langsrud (2005) <doi:10.1007/s11222-005-4789-5>, is used to compute adjusted single response p-values according to familywise error rates and false discovery rates (FDR). The approach to FDR is described in the appendix of Moen et al. (2005) <doi:10.1128/AEM.71.4.2086-2094.2005>. Unbalanced designs are handled by Type II sums of squares as argued in Langsrud (2003) <doi:10.1023/A:1023260610025>. Furthermore, the Type II philosophy is extended to continuous design variables as described in Langsrud et al. (2007) <doi:10.1080/02664760701594246>. This means that the method is invariant to scale changes and that common pitfalls are avoided.
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2025-04-22 |
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r-ffield
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public |
Force field simulation of interaction of set of points. Very useful for placing text labels on graphs, such as scatterplots.
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2025-04-22 |
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r-fextremes
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public |
Provides functions for analysing and modelling extreme events in financial time Series. The topics include: (i) data pre-processing, (ii) explorative data analysis, (iii) peak over threshold modelling, (iv) block maxima modelling, (v) estimation of VaR and CVaR, and (vi) the computation of the extreme index.
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2025-04-22 |
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r-fermicatsr
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public |
Data from various catalogs of astrophysical gamma-ray sources detected by NASA's Large Area Telescope (The Astrophysical Journal, 697, 1071, 2009 June 1), on board the Fermi gamma-ray satellite. More information on Fermi and its data products is available from the Fermi Science Support Center (http://fermi.gsfc.nasa.gov/ssc/).
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2025-04-22 |
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r-fedreporter
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public |
Downloads data from Federal 'RePORTER' <https://api.federalreporter.nih.gov/> using the Federal 'RePORTER' API. Allows the user to search job projects from different government agencies.
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2025-04-22 |
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r-federalregister
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public |
Access data from the Federal Register API <https://www.federalregister.gov/developers/api/v1>.
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2025-04-22 |
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r-featurizer
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public |
A collection of functions that would help one to build features based on external data. Very useful for Data Scientists in data to day work. Many functions create features using parallel computation. Since the nitty gritty of parallel computation is hidden under the hood, the user need not worry about creating clusters and shutting them down.
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2025-04-22 |
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r-fdth
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public |
Perform frequency distribution tables, associated histograms and polygons from vector, data.frame and matrix objects for numerical and categorical variables.
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2025-04-22 |
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r-fdrsampsize
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public |
Defines a collection of functions to compute average power and sample size for studies that use the false discovery rate as the final measure of statistical significance.
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2025-04-22 |
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r-fdrci
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public |
FDR functions for permutation-based estimators, including pi0 as well as FDR confidence intervals. The confidence intervals account for dependencies between tests by the incorporation of an overdispersion parameter, which is estimated from the permuted data.
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2025-04-22 |
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r-fdakma
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public |
It performs simultaneously clustering and alignment of a multidimensional or unidimensional functional dataset by means of k-mean alignment.
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2025-04-22 |
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r-fda
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public |
These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer. They were ported from earlier versions in Matlab and S-PLUS. An introduction appears in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009) Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions of the code and sample analyses are no longer distributed through CRAN, as they were when the book was published. For those, ftp from <http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/> There you find a set of .zip files containing the functions and sample analyses, as well as two .txt files giving instructions for installation and some additional information. The changes from Version 2.4.1 are fixes of bugs in density.fd and removal of functions create.polynomial.basis, polynompen, and polynomial. These were deleted because the monomial basis does the same thing and because there were errors in the code.
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2025-04-22 |
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r-fcmapper
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public |
Provides several functions to create and manipulate fuzzy cognitive maps. It is based on 'FCMapper' for Excel, distributed at <http:// www.fcmappers.net/joomla/>, developed by Michael Bachhofer and Martin Wildenberg. Maps are inputted as adjacency matrices. Attributes of the maps and the equilibrium values of the concepts (including with user-defined constrained values) can be calculated. The maps can be graphed with a function that calls 'igraph'. Multiple maps with shared concepts can be aggregated.
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2025-04-22 |
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r-fcd
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public |
Efficient procedures for community detection in network studies, especially for sparse networks with not very obvious community structure. The algorithms impose penalties on the differences of the coordinates which represent the community labels of the nodes.
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2025-04-22 |
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r-fc
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public |
Provides a streamlined, standard evaluation-based approach to multivariate function composition. Allows for chaining commands via a forward-pipe operator, %>%.
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2025-04-22 |
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r-fbranks
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public |
This package uses time dependent Poisson regression and a record of goals scored in matches to rank teams via estimated attack and defense strengths. The statistical model is based on Dixon and Coles (1997) Modeling Association Football Scores and Inefficiencies in the Football Betting Market, Applied Statistics, Volume 46, Issue 2, 265-280. The package has a some webscrapers to assist in the development and updating of a match database. If the match database contains unconnected clusters (i.e. sets of teams that have only played each other and not played teams from other sets), each cluster is ranked separately relative to the median team strength in the cluster. The package contains functions for predicting and simulating tournaments and leagues from estimated models. The package allows fitting via the glm(), speedglm(), and glmnet() functions. The latter allows fast and efficient fitting of very large numbers of teams. The fitting algorithm will analyze the match data and determine which teams form a cluster (a set of teams where there is a path of matches connecting every team) and fit each cluster separately.
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2025-04-22 |
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r-fbonds
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public |
It implements the Nelson-Siegel and the Nelson-Siegel-Svensson term structures.
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2025-04-22 |
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r-fbn
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public |
Normalizes the data from a file containing the raw values of the SNP probes of microarrray data by using the FISH probes and their corresponding CNs.
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2025-04-22 |
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r-favnums
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public |
A dataset of favourite numbers, selected from an online poll of over 30,000 people by Alex Bellos (http://pages.bloomsbury.com/favouritenumber).
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2025-04-22 |
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r-fastpseudo
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public |
Computes pseudo-observations for survival analysis on right-censored data based on restricted mean survival time.
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2025-04-22 |
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r-fastnaivebayes
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public |
This is an extremely fast implementation of a Naive Bayes classifier. This package is currently the only package that supports a Bernoulli distribution, a Multinomial distribution, and a Gaussian distribution, making it suitable for both binary features, frequency counts, and numerical features. Another feature is the support of a mix of different event models. Only numerical variables are allowed, however, categorical variables can be transformed into dummies and used with the Bernoulli distribution. The implementation is largely based on the paper "A comparison of event models for Naive Bayes anti-spam e-mail filtering" written by K.M. Schneider (2003) <doi:10.3115/1067807>. Any issues can be submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
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2025-04-22 |
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r-fastimputation
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public |
TrainFastImputation() uses training data to describe a multivariate normal distribution that the data approximates or can be transformed into approximating and stores this information as an object of class 'FastImputationPatterns'. FastImputation() function uses this 'FastImputationPatterns' object to impute (make a good guess at) missing data in a single line or a whole data frame of data. This approximates the process used by 'Amelia' <http://gking.harvard.edu/amelia/> but is much faster when filling in values for a single line of data.
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2025-04-22 |
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r-fasthica
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public |
It implements HICA (Hierarchical Independent Component Analysis) algorithm. This approach, obtained through the integration between treelets and Independent Component Analysis, is able to provide a multi-scale non-orthogonal data-driven basis, whose elements have a phenomenological interpretation according to the problem under study.
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2025-04-22 |
