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r-gamlss.data
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public |
Data used as examples to demonstrate GAMLSS models.
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2025-04-22 |
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r-games
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Provides estimation and analysis functions for strategic statistical models.
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2025-04-22 |
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r-gambin
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Fits unimodal and multimodal gambin distributions to species-abundance distributions from ecological data, as in in Matthews et al. (2014) <DOI:10.1111/ecog.00861>. 'gambin' is short for 'gamma-binomial'. The main function is fit_abundances(), which estimates the 'alpha' parameter(s) of the gambin distribution using maximum likelihood. Functions are also provided to generate the gambin distribution and for calculating likelihood statistics.
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2025-04-22 |
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r-gamair
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Data sets and scripts used in the book 'Generalized Additive Models: An Introduction with R', Wood (2006,2017) CRC.
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2025-04-22 |
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r-gaipe
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public |
GAIPE implements graphical representation of accuracy in parameter estimation (AIPE) on RMSEA for sample size planning in structural equation modeling. Sample sizes suggested by RMSEA with AIPE method and power analysis approach can also be obtained separately using the provided functions.
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2025-04-22 |
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r-gains
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Constructs gains tables and lift charts for prediction algorithms. Gains tables and lift charts are commonly used in direct marketing applications. The method is described in Drozdenko and Drake (2002), "Optimal Database Marketing", Chapter 11.
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2025-04-22 |
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r-gadifpt
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In this package we consider Gaussian Diffusion processes and smooth thresholds. After evaluating the mean of the process to check the subthreshold regimen hypothesis, the FPT density function is reconstructed via the numerical quadrature of the integral equation in (Buonocore 1987); first passage times are also generated by the method in (Buonocore 2014) and results are compared. The timestep of the simulations can iteratively be refined. User should provide the functional form for the drift and the infinitesimal variance in the script 'userfunc.R' and for the threshold in the script 'userthresh.R'. All the parameters required by the implementation are to be set in the script 'userparam.R'. Example scripts for common drifts and thresholds are given.
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2025-04-22 |
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r-gad
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This package analyses complex ANOVA models with any combination of orthogonal/nested and fixed/random factors, as described by Underwood (1997). There are two restrictions: (i) data must be balanced; (ii) fixed nested factors are not allowed. Homogeneity of variances is checked using Cochran's C test and 'a posteriori' comparisons of means are done using Student-Newman-Keuls (SNK) procedure.
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2025-04-22 |
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r-g3viz
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R interface for 'g3-lollipop' JavaScript library. Visualize genetic mutation data using an interactive lollipop diagram in RStudio or your browser.
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2025-04-22 |
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r-g1dbn
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public |
G1DBN performs DBN inference using 1st order conditional dependencies.
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2025-04-22 |
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r-fwi.fbp
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Provides three functions to calculate the outputs of the two main components of the Canadian Forest Fire Danger Rating System (CFFDRS): the Fire Weather Index (FWI) System and the Fire Behaviour Prediction (FBP) System.
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2025-04-22 |
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r-fuzzywuzzyr
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Fuzzy string matching implementation of the 'fuzzywuzzy' <https://github.com/seatgeek/fuzzywuzzy> 'python' package. It uses the Levenshtein Distance <https://en.wikipedia.org/wiki/Levenshtein_distance> to calculate the differences between sequences.
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2025-04-22 |
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r-fuzzytoolkituon
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A custom framework for working with Type 1 Fuzzy Logic, produced by the University of Nottingham IMA Group.
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2025-04-22 |
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r-fuzzystattra
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public |
The aim of the package is to provide some basic functions for doing statistics with trapezoidal fuzzy numbers. In particular, the package contains several functions for simulating trapezoidal fuzzy numbers, as well as for calculating some central tendency measures (mean and two types of median), some scale measures (variance, ADD, MDD, Sn, Qn, Tn and some M-estimators) and one diversity index and one inequality index. Moreover, functions for calculating the 1-norm distance, the mid/spr distance and the (phi,theta)-wabl/ldev/rdev distance between fuzzy numbers are included, and a function to calculate the value phi-wabl given a sample of trapezoidal fuzzy numbers.
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2025-04-22 |
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r-fuzzysim
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Functions to calculate fuzzy versions of species' occurrence patterns based on presence-absence data (including inverse distance interpolation, trend surface analysis and prevalence-independent favourability GLM), and pair-wise fuzzy similarity (based on fuzzy versions of commonly used similarity indices) among those occurrence patterns. Includes also functions for model comparison (overlap and fuzzy similarity, loss or gain), and for data preparation, such as obtaining unique abbreviations of species names, converting species lists (long format) to presence-absence tables (wide format), transposing part of a data frame, assessing the false discovery rate, or analysing and dealing with multicollinearity among variables. Includes also sample datasets for providing practical examples.
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2025-04-22 |
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r-fuzzyr
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Design and simulate fuzzy logic systems using Type 1 Fuzzy Logic. This toolkit includes with graphical user interface (GUI) and an adaptive neuro- fuzzy inference system (ANFIS). This toolkit is a continuation from the previous package ('FuzzyToolkitUoN'). Produced by the Intelligent Modelling & Analysis Group, University of Nottingham.
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2025-04-22 |
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r-fuzzynumbers
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S4 classes and methods to deal with fuzzy numbers. They allow for computing any arithmetic operations (e.g., by using the Zadeh extension principle), performing approximation of arbitrary fuzzy numbers by trapezoidal and piecewise linear ones, preparing plots for publications, computing possibility and necessity values for comparisons, etc.
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2025-04-22 |
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r-fuzzyfdr
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Exact calculation of fuzzy decision rules for multiple testing. Choose to control FDR (false discovery rate) using the Benjamini and Hochberg method, or FWER (family wise error rate) using the Bonferroni method. Kulinsakaya and Lewin (2007).
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2025-04-22 |
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r-fuzzyahp
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Calculation of AHP (Analytic Hierarchy Process - <http://en.wikipedia.org/wiki/Analytic_hierarchy_process>) with classic and fuzzy weights based on Saaty's pairwise comparison method for determination of weights.
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2025-04-22 |
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r-futility
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Randomized clinical trials commonly follow participants for a time-to-event efficacy endpoint for a fixed period of time. Consequently, at the time when the last enrolled participant completes their follow-up, the number of observed endpoints is a random variable. Assuming data collected through an interim timepoint, simulation-based estimation and inferential procedures in the standard right-censored failure time analysis framework are conducted for the distribution of the number of endpoints--in total as well as by treatment arm--at the end of the follow-up period. The future (i.e., yet unobserved) enrollment, endpoint, and dropout times are generated according to mechanisms specified in the simTrial() function in the 'seqDesign' package. A Bayesian model for the endpoint rate, offering the option to specify a robust mixture prior distribution, is used for generating future data (see the vignette for details). Inference can be restricted to participants who received treatment according to the protocol and are observed to be at risk for the endpoint at a specified timepoint. Plotting functions are provided for graphical display of results.
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2025-04-22 |
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r-futile.options
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A scoped options management framework. Used in other packages.
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2025-04-22 |
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r-fusionlearn
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The fusion learning method uses a model selection algorithm to learn from multiple data sets across different experimental platforms through group penalization. The responses of interest may include a mix of discrete and continuous variables. The responses may share the same set of predictors, however, the models and parameters differ across different platforms. Integrating information from different data sets can enhance the power of model selection. Package is based on Xin Gao, Raymond J. Carroll (2017) <arXiv:1610.00667v1>.
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2025-04-22 |
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r-fusionclust
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Provides the Big Merge Tracker and COSCI algorithms for convex clustering and feature screening using L1 fusion penalty. See Radchenko, P. and Mukherjee, G. (2017) <doi:10.1111/rssb.12226> and T.Banerjee et al. (2017) <doi:10.1016/j.jmva.2017.08.001> for more details.
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2025-04-22 |
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r-funta
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Computes the functional tangential angle pseudo-depth and its robustified version from the paper by Kuhnt and Rehage (2016). See Kuhnt, S.; Rehage, A. (2016): An angle-based multivariate functional pseudo-depth for shape outlier detection, JMVA 146, 325-340, <doi:10.1016/j.jmva.2015.10.016> for details.
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2025-04-22 |
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r-funreg
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Performs functional regression, and some related approaches, for intensive longitudinal data (see the book by Walls & Schafer, 2006, Models for Intensive Longitudinal Data, Oxford) when such data is not necessarily observed on an equally spaced grid of times. The approach generally follows the ideas of Goldsmith, Bobb, Crainiceanu, Caffo, and Reich (2011)<DOI:10.1198/jcgs.2010.10007> and the approach taken in their sample code, but with some modifications to make it more feasible to use with long rather than wide, non-rectangular longitudinal datasets with unequal and potentially random measurement times. It also allows easy plotting of the correlation between the smoothed covariate and the outcome as a function of time, which can add additional insights on how to interpret a functional regression. Additionally, it also provides several permutation tests for the significance of the functional predictor. The heuristic interpretation of ``time'' is used to describe the index of the functional predictor, but the same methods can equally be used for another unidimensional continuous index, such as space along a north-south axis. The development of this package was part of a research project supported by Award R03 CA171809-01 from the National Cancer Institute and Award P50 DA010075 from the National Institute on Drug Abuse. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Cancer Institute, or the National Institutes of Health.
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2025-04-22 |
