|
r-grplasso
|
public |
Fits user-specified (GLM-) models with group lasso penalty.
|
2023-06-16 |
|
r-grimport2
|
public |
Functions for importing external vector images and drawing them as part of 'R' plots. This package is different from the 'grImport' package because, where that package imports 'PostScript' format images, this package imports 'SVG' format images. Furthermore, this package imports a specific subset of 'SVG', so external images must be preprocessed using a package like 'rsvg' to produce 'SVG' that this package can import. 'SVG' features that are not supported by 'R' graphics, e.g., gradient fills, can be imported and then exported via the 'gridSVG' package.
|
2023-06-16 |
|
r-grassmannoptim
|
public |
Optimizing a function F(U), where U is a semi-orthogonal matrix and F is invariant under an orthogonal transformation of U
|
2023-06-16 |
|
r-gradientpickerd3
|
public |
Widget for an interactive selection and modification of a color gradient. 'gradientPickerD3' allows addition, removement and replacement of color ticks. List of numeric values will automatically translate in their corresponding tick position within the numeric range. App returns a data.frame containing tick values, colors and the positions in percent (0.0 to 1.0) for each color tick in the gradient. The original JS 'jquery-gradient-picker' was implemented by Matt Crinklaw-Vogt (nick: tantaman) <https://github.com/tantaman/>. Widget and JS modifications were done by CD. Peikert.
|
2023-06-16 |
|
r-goric
|
public |
Generalized Order-Restricted Information Criterion (GORIC) value for a set of hypotheses in multivariate linear models and generalised linear models.
|
2023-06-16 |
|
r-gnorm
|
public |
Functions for obtaining generalized normal/exponential power distribution probabilities, quantiles, densities and random deviates. The generalized normal/exponential power distribution was introduced by Subbotin (1923) and rediscovered by Nadarajah (2005). The parametrization given by Nadarajah (2005) <doi:10.1080/02664760500079464> is used.
|
2023-06-16 |
|
r-gmdh
|
public |
Group method of data handling (GMDH) - type neural network algorithm is the heuristic self-organization method for modelling the complex systems. In this package, GMDH-type neural network algorithms are applied to make short term forecasting for a univariate time series.
|
2023-06-16 |
|
r-gim
|
public |
Implements the generalized integration model, which integrates individual-level data and summary statistics under a generalized linear model framework. It supports continuous and binary outcomes to be modeled by the linear and logistic regression models.
|
2023-06-16 |
|
r-ghibli
|
public |
Colour palettes inspired by Studio Ghibli <https://en.wikipedia.org/wiki/Studio_Ghibli> films, ported to R for your enjoyment.
|
2023-06-16 |
|
r-ggplot2movies
|
public |
A dataset about movies. This was previously contained in ggplot2, but has been moved its own package to reduce the download size of ggplot2.
|
2023-06-16 |
|
r-gepaf
|
public |
Encode and decode the Google Encoded Polyline Algorithm Format (<https://developers.google.com/maps/documentation/utilities/polylinealgorithm>).
|
2023-06-16 |
|
r-geomapdata
|
public |
Set of data for use in package GEOmap. Includes world map, USA map, Coso map, Japan Map, ETOPO5
|
2023-06-16 |
|
r-gaussfacts
|
public |
Display a random fact about Carl Friedrich Gauss based the on collection curated by Mike Cavers via the <http://gaussfacts.com> site.
|
2023-06-16 |
|
r-gds
|
public |
Contains a function called gds() which accepts three input parameters like lower limits, upper limits and the frequencies of the corresponding classes. The gds() function calculate and return the values of mean ('gmean'), median ('gmedian'), mode ('gmode'), variance ('gvar'), standard deviation ('gstdev'), coefficient of variance ('gcv'), quartiles ('gq1', 'gq2', 'gq3'), inter-quartile range ('gIQR'), skewness ('g1'), and kurtosis ('g2') which facilitate effective data analysis. For skewness and kurtosis calculations we use moments.
|
2023-06-16 |
|
r-generaloaxaca
|
public |
Perform the Blinder-Oaxaca decomposition for generalized linear model with bootstrapped standard errors. The twofold and threefold decomposition are given, even the generalized linear model output in each group.
|
2023-06-16 |
|
r-gaparsimony
|
public |
Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) <DOI:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.
|
2023-06-16 |
|
r-gar
|
public |
The functions included are used to obtain initial authentication with Google Analytics as well as simple and organized data retrieval from the API. Allows for retrieval from multiple profiles at once.
|
2023-06-16 |
|
r-g.data
|
public |
Create and maintain delayed-data packages (ddp's). Data stored in a ddp are available on demand, but do not take up memory until requested. You attach a ddp with g.data.attach(), then read from it and assign to it in a manner similar to S-PLUS, except that you must run g.data.save() to actually commit to disk.
|
2023-06-16 |
|
r-gclus
|
public |
Orders panels in scatterplot matrices and parallel coordinate displays by some merit index. Package contains various indices of merit, ordering functions, and enhanced versions of pairs and parcoord which color panels according to their merit level.
|
2023-06-16 |
|
r-gbrd
|
public |
Provides utilities for processing Rd objects and files. Extract argument descriptions and other parts of the help pages of functions.
|
2023-06-16 |
|
r-gap.datasets
|
public |
Datasets associated with the 'gap' package. Currently, it includes an example data for regional association plot (CDKN), an example data for a genomewide association meta-analysis (OPG), Manhattan plots with (hr1420, mhtdata) and without (w4) gene annotations.
|
2023-06-16 |
|
r-gcookbook
|
public |
Data sets used in the book "R Graphics Cookbook" by Winston Chang, published by O'Reilly Media.
|
2023-06-16 |
|
r-fwi.fbp
|
public |
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.
|
2023-06-16 |
|
r-funique
|
public |
Similar to base's unique function, only optimized for working with data frames, especially those that contain date-time columns.
|
2023-06-16 |
|
r-fmp
|
public |
Estimates Filtered Monotonic Polynomial IRT Models as described by Liang and Browne (2015) <DOI:10.3102/1076998614556816>.
|
2023-06-16 |
|
r-flower
|
public |
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.
|
2023-06-16 |
|
r-fixseqmtp
|
public |
Several generalized / directional Fixed Sequence Multiple Testing Procedures (FSMTPs) are developed for testing a sequence of pre-ordered hypotheses while controlling the FWER, FDR and Directional Error (mdFWER). All three FWER controlling generalized FSMTPs are designed under arbitrary dependence, which allow any number of acceptances. Two FDR controlling generalized FSMTPs are respectively designed under arbitrary dependence and independence, which allow more but a given number of acceptances. Two mdFWER controlling directional FSMTPs are respectively designed under arbitrary dependence and independence, which can also make directional decisions based on the signs of the test statistics. The main functions for each proposed generalized / directional FSMTPs are designed to calculate adjusted p-values and critical values, respectively. For users' convenience, the functions also provide the output option for printing decision rules.
|
2023-06-16 |
|
r-fermicatsr
|
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/).
|
2023-06-16 |
|
r-federalregister
|
public |
Access data from the Federal Register API <https://www.federalregister.gov/developers/api/v1>.
|
2023-06-16 |
|
r-fasjem
|
public |
This is an R implementation of "A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models" (FASJEM). The FASJEM algorithm can be used to estimate multiple related precision matrices. For instance, it can identify context-specific gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogonous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(fasjem) to learn the basic functions provided by this package. For more details, please see <http://proceedings.mlr.press/v54/wang17e/wang17e.pdf>.
|
2023-06-16 |
|
r-faraway
|
public |
Books are "Practical Regression and ANOVA in R" on CRAN, "Linear Models with R" published 1st Ed. August 2004, 2nd Ed. July 2014 by CRC press, ISBN 9781439887332, and "Extending the Linear Model with R" published by CRC press in 1st Ed. December 2005 and 2nd Ed. March 2016, ISBN 9781584884248.
|
2023-06-16 |
|
r-faisalconjoint
|
public |
It is used for systematic analysis of decisions based on attributes and its levels.
|
2023-06-16 |
|
r-expde
|
public |
Modular implementation of the Differential Evolution algorithm for experimenting with different types of operators.
|
2023-06-16 |
|
r-etma
|
public |
Traditional meta-regression based method has been developed for using meta-analysis data, but it faced the challenge of inconsistent estimates. This package purpose a new statistical method to detect epistasis using incomplete information summary, and have proven it not only successfully let consistency of evidence, but also increase the power compared with traditional method (Detailed tutorial is shown in website).
|
2023-06-16 |
|
r-futility
|
public |
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.
|
2023-06-16 |
|
r-fraction
|
public |
This is the package which can help you turn numeric,dataframe,matrix into fraction form.
|
2023-06-16 |
|
r-fracprolif
|
public |
Functions for fitting data to a quiescent growth model, i.e. a growth process that involves members of the population who stop dividing or propagating.
|
2023-06-16 |
|
r-foresthes
|
public |
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.
|
2023-06-16 |
|
r-fixedpoint
|
public |
For functions that take and return vectors (or scalars), this package provides 8 algorithms for finding fixed point vectors (vectors for which the inputs and outputs to the function are the same vector). These algorithms include Anderson (1965) acceleration <doi:10.1145/321296.321305>, epsilon extrapolation methods (Wynn 1962 <doi:10.2307/2004051>) and minimal polynomial methods (Cabay and Jackson 1976 <doi:10.1137/0713060>).
|
2023-06-16 |
|
r-fimport
|
public |
Provides a collection of utility functions to download and manage data sets from the Internet or from other sources.
|
2023-06-16 |
|
r-fiberld
|
public |
Routines for estimating tree fiber (tracheid) length distributions in the standing tree based on increment core samples. Two types of data can be used with the package, increment core data measured by means of an optical fiber analyzer (OFA), e.g. such as the Kajaani Fiber Lab, or measured by microscopy. Increment core data analyzed by OFAs consist of the cell lengths of both cut and uncut fibres (tracheids) and fines (such as ray parenchyma cells) without being able to identify which cells are cut or if they are fines or fibres. The microscopy measured data consist of the observed lengths of the uncut fibres in the increment core. A censored version of a mixture of the fine and fiber length distributions is proposed to fit the OFA data, under distributional assumptions (Svensson et al., 2006) <doi:10.1111/j.1467-9469.2006.00501.x>. The package offers two choices for the assumptions of the underlying density functions of the true fiber (fine) lenghts of those fibers (fines) that at least partially appear in the increment core, being the generalized gamma and the log normal densities.
|
2023-06-16 |
|
r-fdakma
|
public |
It performs simultaneously clustering and alignment of a multidimensional or unidimensional functional dataset by means of k-mean alignment.
|
2023-06-16 |
|
r-fancycut
|
public |
Provides the function fancycut() which is like cut() except you can mix left open and right open intervals with point values, intervals that are closed on both ends and intervals that are open on both ends.
|
2023-06-16 |
|
r-ezknitr
|
public |
An extension of 'knitr' that adds flexibility in several ways. One common source of frustration with 'knitr' is that it assumes the directory where the source file lives should be the working directory, which is often not true. 'ezknitr' addresses this problem by giving you complete control over where all the inputs and outputs are, and adds several other convenient features to make rendering markdown/HTML documents easier.
|
2023-06-16 |
|
r-evcombr
|
public |
Package for combining pieces of evidence
|
2023-06-16 |
|
r-etseed
|
public |
Client to interact with the 'etcd' 'key-value' data store <https://github.com/coreos/etcd>. Functions included for managing directories, keys, nodes, and getting statistics.
|
2023-06-16 |
|
r-es
|
public |
Implementation of the Edge Selection Algorithm
|
2023-06-16 |
|
r-estout
|
public |
This package is intended to speedup the process of creating model-comparing tables common in Macroeconomics. The function collection stores the estimates of several models and formats it to a table of the form estimate starred and std.err. below. The default output is LaTeX but output to CSV for later editing in a spreadsheet tool is possible as well. It works for linear models (lm) and panel models from the "plm"-package (plm). Two further implemented functions "descsto" and "desctab" enable you to export descriptive statistics of data-frames and single variables to LaTeX and CSV.
|
2023-06-16 |
|
r-games
|
public |
Provides estimation and analysis functions for strategic statistical models.
|
2023-06-16 |
|
r-gains
|
public |
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.
|
2023-06-16 |
