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r-forestplot
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A forest plot that allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more. The aim is to extend the use of forest plots beyond meta-analyses. This is a more general version of the original 'rmeta' package's forestplot() function and relies heavily on the 'grid' package.
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2025-04-22 |
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r-foresthes
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Assessing forest ecosystem health is an effective way for forest resource management.The national forest health evaluation system at the forest stand level using analytic hierarchy process, has a high application value and practical significance. The package can effectively and easily realize the total assessment process, and help foresters to further assess and management forest resources.
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2025-04-22 |
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r-forestfit
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Developed for the following tasks. I) Computing the probability density function, cumulative distribution function, random generation, and estimating the parameters of the eleven mixture models including mixture of Birnbaum-Saunders, BurrXII, Chen, F, Frechet, gamma, Gompertz, log-logistic, log-normal, Lomax, and Weibull. II) Point estimation of the parameters of two- and three-parameter Weibull distributions. In the case of two-parameter, twelve methods consist of generalized least square type 1, generalized least square type 2, L-moment, maximum likelihood, logarithmic moment, moment, percentile, rank correlation, least square, weighted maximum likelihood, U-statistic, weighted least square are used and investigated methods for the three-parameter case are: maximum likelihood, modified moment type 1, modified moment type 2, modified moment type 3, modified maximum likelihood type 1, modified maximum likelihood type 2, modified maximum likelihood type 3, modified maximum likelihood type 4, moment, maximum product spacing, T-L moment, and weighted maximum likelihood. III) The Bayesian estimators of the three-parameter Weibull distribution. IV) Estimating parameters of the three-parameter Weibull distribution fitted to grouped data using three methods including approximated maximum likelihood, expectation maximization, and maximum likelihood. V) Estimating the parameters of the gamma, log-normal, and Weibull mixture models fitted to the grouped data through the EM algorithm. VI) Estimating parameters of the non-linear growth curve fitted to the height-diameter observations.
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2025-04-22 |
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r-forecastcombinations
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Aim: Supports the most frequently used methods to combine forecasts. Among others: Simple average, Ordinary Least Squares, Least Absolute Deviation, Constrained Least Squares, Variance-based, Best Individual model, Complete subset regressions and Information-theoretic (information criteria based).
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2025-04-22 |
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r-foolbox
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Provides functionality for manipulating functions and translating them in metaprogramming.
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2025-04-22 |
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r-fontliberation
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A placeholder for the Liberation fontset intended for the `fontquiver` package. This fontset covers the 12 combinations of families (sans, serif, mono) and faces (plain, bold, italic, bold italic) supported in R graphics devices.
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2025-04-22 |
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r-fontcm
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Computer Modern font for use with extrafont package
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2025-04-22 |
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r-fontbitstreamvera
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Provides fonts licensed under the 'Bitstream Vera Fonts' license for the 'fontquiver' package.
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2025-04-22 |
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r-folderfun
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If you find yourself working on multiple different projects in R, you'll want a series of folders pointing to raw data, processed data, plot results, intermediate table outputs, etc. This package makes it easier to do that by providing a quick and easy way to create and use functions for project-level directories.
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2025-04-22 |
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r-focusedmds
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Takes a distance matrix and plots it as an interactive graph. One point is focused at the center of the graph, around which all other points are plotted in their exact distances as given in the distance matrix. All other non-focus points are plotted as best as possible in relation to one another. Double click on any point to choose a new focus point, and hover over points to see their ID labels. If color label categories are given, hover over colors in the legend to highlight only those points and click on colors to highlight multiple groups. For more information on the rationale and mathematical background, as well as an interactive introduction, see <https://lea-urpa.github.io/focusedMDS.html>.
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2025-04-22 |
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r-foba
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foba is a package that implements forward, backward, and foba sparse learning algorithms for ridge regression, described in the paper "Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations".
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2025-04-22 |
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r-fmsmsnreg
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Fit linear regression models where the random errors follow a finite mixture of of Skew Heavy-Tailed Errors.
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2025-04-22 |
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r-fmsb
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Several utility functions for the book entitled "Practices of Medical and Health Data Analysis using R" (Pearson Education Japan, 2007) with Japanese demographic data and some demographic analysis related functions.
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2025-04-22 |
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r-fmp
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Estimates Filtered Monotonic Polynomial IRT Models as described by Liang and Browne (2015) <DOI:10.3102/1076998614556816>.
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2025-04-22 |
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r-fmdates
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Implements common date calculations relevant for specifying the economic nature of financial market contracts that are typically defined by International Swap Dealer Association (ISDA, <http://www2.isda.org>) legal documentation. This includes methods to check whether dates are business days in certain locales, functions to adjust and shift dates and time length (or day counter) calculations.
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2025-04-22 |
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r-fmcmc
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Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425).
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2025-04-22 |
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r-fluxweb
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Compute energy fluxes in trophic networks, from resources to their consumers, and can be applied to systems ranging from simple two-species interactions to highly complex food webs. It implements the approach described in Gauzens et al. (2017) <doi:10.1101/229450> to calculate energy fluxes, which are also used to calculate equilibrium stability.
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2025-04-22 |
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r-flux
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Functions for the calculation of greenhouse gas flux rates from closed chamber concentration measurements. The package follows a modular concept: Fluxes can be calculated in just two simple steps or in several steps if more control in details is wanted. Additionally plot and preparation functions as well as functions for modelling gpp and reco are provided.
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2025-04-22 |
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r-flury
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Contains data sets from Bernard Flury (1997) A First Course in Multivariate Statistics, Springer NY
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2025-04-22 |
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r-fluosurv
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Use spectrophotometry measurements performed on insects as a way to infer pathogens virulence. Insect movements cause fluctuations in fluorescence signal, and functions are provided to estimate when the insect has died as the moment when variance in autofluorescence signal drops to zero. The package provides functions to obtain this estimate together with functions to import spectrophotometry data from a Biotek microplate reader. Details of the method are given in Parthuisot et al. (2018) <doi:10.1101/297929>.
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2025-04-22 |
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r-flr
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FLR algorithm for classification
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2025-04-22 |
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r-flows
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Selections on flow matrices, statistics on selected flows, map and graph visualisations.
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2025-04-22 |
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r-flowregenvcost
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An application to calculate the daily environmental costs of river flow regulation by dams based on GarcÃa de Jalon et al. 2017 <doi:10.1007/s11269-017-1663-0>.
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2025-04-22 |
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r-flowfield
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Flow field forecasting draws information from an interpolated flow field of the observed time series to incrementally build a forecast.
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2025-04-22 |
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r-flower
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Flowering is an important life history trait of flowering plants. It has been mainly analyzed with respect to flowering onset and duration of flowering. This tools provide some functions to compute the temporal distribution of an flowering individual related to other population members. fCV() measures the temporal variation in flowering. RIind() measures the rank order of flowering for individual plants within a population. SI(), SI2(), SI3(), and SI4() calculate flowering synchrony with different methods.
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2025-04-22 |
