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r-knitrprogressbar
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Provides a progress bar similar to 'dplyr' that can write progress out to a variety of locations, including stdout(), stderr(), or from file(). Useful when using 'knitr' or 'rmarkdown', and you still want to see progress of calculations in the terminal.
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2024-01-16 |
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r-knitrbootstrap
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A framework to create Bootstrap <http://getbootstrap.com/> HTML reports from 'knitr' 'rmarkdown'.
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2024-01-16 |
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r-knitlatex
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Provides several helper functions for working with 'knitr' and 'LaTeX'. It includes 'xTab' for creating traditional 'LaTeX' tables, 'lTab' for generating 'longtable' environments, and 'sTab' for generating a 'supertabular' environment. Additionally, this package contains a knitr_setup() function which fixes a well-known bug in 'knitr', which distorts the 'results="asis"' command when used in conjunction with user-defined commands; and a com command (<<com=TRUE>>=) which renders the output from 'knitr' as a 'LaTeX' command.
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2024-01-16 |
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r-knapsacksampling
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The sampl.mcmc() function creates samples of the feasible region of a knapsack problem with both equalities and inequalities constraints.
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2024-01-16 |
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r-kmsurv
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Data sets and functions for Klein and Moeschberger (1997), "Survival Analysis, Techniques for Censored and Truncated Data", Springer.
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2024-01-16 |
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r-kmodr
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An implementation of the 'k-means--' algorithm proposed by Chawla and Gionis, 2013 in their paper, "k-means-- : A unified approach to clustering and outlier detection. SIAM International Conference on Data Mining (SDM13)", <doi:10.1137/1.9781611972832.21> and using 'ordering' described by Howe, 2013 in the thesis, Clustering and anomaly detection in tropical cyclones". Useful for creating (potentially) tighter clusters than standard k-means and simultaneously finding outliers inexpensively in multidimensional space.
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2024-01-16 |
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r-km.ci
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Computes various confidence intervals for the Kaplan-Meier estimator, namely: Peto's CI, Rothman CI, CI's based on Greenwood's variance, Thomas and Grunkemeier CI and the simultaneous confidence bands by Nair and Hall and Wellner.
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2024-01-16 |
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r-kernelshap
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Efficient implementation of Kernel SHAP, see Lundberg and Lee (2017), and Covert and Lee (2021) <http://proceedings.mlr.press/v130/covert21a>. For models with up to eight features, the results are exact regarding the selected background data. Otherwise, an almost exact hybrid algorithm involving iterative sampling is used. The package plays well together with meta-learning packages like 'tidymodels', 'caret' or 'mlr3'. Visualizations can be done using the R package 'shapviz'.
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2024-01-16 |
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r-klustr
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Used to create dynamic, interactive 'D3.js' based parallel coordinates and principal component plots in 'R'. The plots make visualizing k-means or other clusters simple and informative.
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2024-01-16 |
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r-kirby21.base
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Multi-modal magnetic resonance imaging ('MRI') data from the 'Kirby21' 'reproducibility' study <https://www.nitrc.org/projects/multimodal/>, including functional and structural imaging.
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2024-01-16 |
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r-kinship2
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Routines to handle family data with a pedigree object. The initial purpose was to create correlation structures that describe family relationships such as kinship and identity-by-descent, which can be used to model family data in mixed effects models, such as in the coxme function. Also includes a tool for pedigree drawing which is focused on producing compact layouts without intervention. Recent additions include utilities to trim the pedigree object with various criteria, and kinship for the X chromosome.
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2024-01-16 |
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r-kin.cohort
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Analysis of kin-cohort studies. kin.cohort provides estimates of age-specific cumulative risk of a disease for carriers and noncarriers of a mutation. The cohorts are retrospectively built from relatives of probands for whom the genotype is known. Currently the method of moments and marginal maximum likelihood are implemented. Confidence intervals are calculated from bootstrap samples. Most of the code is a translation from previous 'MATLAB' code by N. Chatterjee.
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2024-01-16 |
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r-kimisc
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A collection of useful functions not found anywhere else, mainly for programming: Pretty intervals, generalized lagged differences, checking containment in an interval, and an alternative interface to assign().
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2024-01-16 |
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r-kidney.epi
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Contains kidney care oriented functions. Current version contains functions for calculation of: - Kidney Donor Risk Index and Kidney Donor Profile Index for kidney transplant donors by Rao et al. (2009) <doi:10.1097/TP.0b013e3181ac620b>. - Estimated glomerular filtration rate by CKD-EPI, MDRD and other equations. Citation: Bikbov B. R open source programming code for calculation of the Kidney Donor Profile Index and Kidney Donor Risk Index. Kidney Diseases (2018) 4:269–272 <doi:10.1159/000492427> (the only citation for the whole package).
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2024-01-16 |
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r-kgc
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Aids in identifying the Koeppen-Geiger (KG) climatic zone for a given location. The Koeppen-Geiger climate zones were first published in 1884, as a system to classify regions of the earth by their relative heat and humidity through the year, for the benefit of human health, plant and agriculture and other human activity [1]. This climate zone classification system, applicable to all of the earths surface, has continued to be developed by scientists up to the present day. Recently one of use (FZ) has published updated, higher accuracy KG climate zone definitions [2]. In this package we use these updated high-resolution maps as the data source [3]. We provide functions that return the KG climate zone for a given longitude and lattitude, or for a given United States zip code. In addition the CZUncertainty() function will check climate zones nearby to check if the given location is near a climate zone boundary. In addition an interactive shiny app is provided to define the KG climate zone for a given longitude and lattitude, or United States zip code. Digital data, as well as animated maps, showing the shift of the climate zones are provided on the following website <http://koeppen-geiger.vu-wien.ac.at>. This work was supported by the DOE-EERE SunShot award DE-EE-0007140. [1] W. Koeppen, (2011) <doi:10.1127/0941-2948/2011/105>. [2] F. Rubel and M. Kottek, (2010) <doi:10.1127/0941-2948/2010/0430>. [3] F. Rubel, K. Brugger, K. Haslinger, and I. Auer, (2016) <doi:10.1127/metz/2016/0816>.
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2024-01-16 |
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r-katex
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Convert latex math expressions to HTML and 'MathML' for use in markdown documents or package manual pages. The rendering is done in R using the V8 engine (i.e. server-side), which eliminates the need for embedding the 'MathJax' library into your web pages. In addition a 'math-to-rd' wrapper is provided to automatically render beautiful math in R documentation files.
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2024-01-16 |
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r-keyringr
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Decrypts passwords stored in the Gnome Keyring, macOS Keychain and strings encrypted with the Windows Data Protection API.
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2024-01-16 |
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r-kfigr
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A streamlined cross-referencing system for R Markdown documents generated with 'knitr'. R Markdown is an authoring format for generating dynamic content from R. 'kfigr' provides a hook for anchoring code chunks and a function to cross-reference document elements generated from said chunks, e.g. figures and tables.
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2024-01-16 |
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r-kfda
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Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) <DOI:10.1016/j.patcog.2003.10.015>.
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2024-01-16 |
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r-keras
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Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
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2024-01-16 |
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r-kernscr
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Kernel Machine Score Test for Pathway Analysis in the Presence of Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) <doi: 10.1177/0962280216653427>.
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2024-01-16 |
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r-keep
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Provides arrays with flexible control over dimension dropping when subscripting.
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2024-01-16 |
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r-jtools
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This is a collection of tools for more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Support for models produced by the survey and lme4 packages are points of emphasis.
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2024-01-16 |
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r-jwileymisc
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Miscellaneous tools and functions, including: generate descriptive statistics tables, format output, visualize relations among variables or check distributions, and generic functions for residual and model diagnostics.
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2024-01-16 |
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r-kdist
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Density, distribution function, quantile function and random generation for the K-distribution. A plotting function that plots data on Weibull paper and another function to draw additional lines. See results from package in T Lamont-Smith (2018), submitted J. R. Stat. Soc.
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2024-01-16 |
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r-kdensity
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Handles univariate non-parametric density estimation with parametric starts and asymmetric kernels in a simple and flexible way. Kernel density estimation with parametric starts involves fitting a parametric density to the data before making a correction with kernel density estimation, see Hjort & Glad (1995) <doi:10.1214/aos/1176324627>. Asymmetric kernels make kernel density estimation more efficient on bounded intervals such as (0, 1) and the positive half-line. Supported asymmetric kernels are the gamma kernel of Chen (2000) <doi:10.1023/A:1004165218295>, the beta kernel of Chen (1999) <doi:10.1016/S0167-9473(99)00010-9>, and the copula kernel of Jones & Henderson (2007) <doi:10.1093/biomet/asm068>. User-supplied kernels, parametric starts, and bandwidths are supported.
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2024-01-16 |
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r-kappasize
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Contains basic tools for sample size estimation in studies of interobserver/interrater agreement (reliability). Includes functions for both the power-based and confidence interval-based methods, with binary or multinomial outcomes and two through six raters.
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2024-01-16 |
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r-juliaconnector
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Allows to import functions and whole packages from 'Julia' in R. Imported 'Julia' functions can directly be called as R functions. Data structures can be translated between 'Julia' and R. More details can also be found in the corresponding article <doi:10.18637/jss.v101.i06>.
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2024-01-16 |
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r-kaphom
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Tests the homogeneity of intraclass kappa statistics obtained from independent studies or a stratified study with binary results. It is desired to compare the kappa statistics obtained in multi-center studies or in a single stratified study to give a common or summary kappa using all available information. If the homogeneity test of these kappa statistics is not rejected, then it is possible to make inferences over a single kappa statistic that summarizes all the studies. Muammer Albayrak, Kemal Turhan, Yasemin Yavuz, Zeliha Aydin Kasap (2019) <doi:10.1080/03610918.2018.1538457> Jun-mo Nam (2003) <doi:10.1111/j.0006-341X.2003.00118.x> Jun-mo Nam (2005) <doi:10.1002/sim.2321>Mousumi Banerjee, Michelle Capozzoli, Laura McSweeney,Debajyoti Sinha (1999) <doi:10.2307/3315487> Allan Donner, Michael Eliasziw, Neil Klar (1996) <doi:10.2307/2533154>.
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2024-01-16 |
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r-kader
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Implementation of various kernel adaptive methods in nonparametric curve estimation like density estimation as introduced in Stute and Srihera (2011) <doi:10.1016/j.spl.2011.01.013> and Eichner and Stute (2013) <doi:10.1016/j.jspi.2012.03.011> for pointwise estimation, and like regression as described in Eichner and Stute (2012) <doi:10.1080/10485252.2012.760737>.
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2024-01-16 |
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r-kableextra
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Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.
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2024-01-16 |
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r-juicyjuice
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There are occasions where you need a piece of HTML with integrated styles. A prime example of this is HTML email. This transformation involves moving the CSS and associated formatting instructions from the style block in the head of your document into the body of the HTML. Many prominent email clients require integrated styles in HTML email; otherwise a received HTML email will be displayed without any styling. This package will quickly and precisely perform these CSS transformations when given HTML text and it does so by using the JavaScript 'juice' library.
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2024-01-16 |
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r-jvnvar
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Many method to compute, predict and back-test VaR. For more detail, see the report: Value at Risk <researchgate.net>.
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2024-01-16 |
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r-jvcoords
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Provides functions to standardize and whiten data, and to perform Principal Component Analysis (PCA). The main advantage of this package over alternatives like prcomp() is, that jvcoords makes it easy to convert (additional) data between the original and the transformed coordinates. The package also provides a class coords, which can represent affine coordinate transformations. This class forms the basis of the transformations provided by the package, but can also be used independently. The implementation has been optimized to be of comparable speed (and sometimes even faster) than existing alternatives.
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2024-01-16 |
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r-jstable
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Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.
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2024-01-16 |
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r-julia
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Generates image data for fractals (Julia and Mandelbrot sets) on the complex plane in the given region and resolution. Benoit B Mandelbrot (1982).
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2024-01-16 |
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r-jstree
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Create and customize interactive trees using the 'jQuery' 'jsTree' <https://www.jstree.com/> plugin library and the 'htmlwidgets' package. These trees can be used directly from the R console, from 'RStudio', in Shiny apps and R Markdown documents.
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2024-01-16 |
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r-jskm
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The function 'jskm()' creates publication quality Kaplan-Meier plot with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier estimator.
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2024-01-16 |
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r-js
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A set of utilities for working with JavaScript syntax in R. Includes tools to parse, tokenize, compile, validate, reformat, optimize and analyze JavaScript code.
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2024-01-16 |
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r-jsmodule
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'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
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2024-01-16 |
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r-jsonvalidate
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Uses the node library 'is-my-json-valid' or 'ajv' to validate 'JSON' against a 'JSON' schema. Drafts 04, 06 and 07 of 'JSON' schema are supported.
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2024-01-16 |
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r-jsonld
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JSON-LD is a light-weight syntax for expressing linked data. It is primarily intended for web-based programming environments, interoperable web services and for storing linked data in JSON-based databases. This package provides bindings to the JavaScript library for converting, expanding and compacting JSON-LD documents.
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2024-01-16 |
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r-json64
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Encode/Decode 'base64', with support for JSON format, using two functions: j_encode() and j_decode(). 'Base64' is a group of similar binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix-64 representation, used when there is a need to encode binary data that needs to be stored and transferred over media that are designed to deal with textual data, ensuring that the data will remain intact and without modification during transport. <https://developer.mozilla.org/en-US/docs/Web/API/WindowBase64/Base64_encoding_and_decoding> On the other side, JSON (JavaScript Object Notation) is a lightweight data-interchange format. Easy to read, write, parse and generate. It is based on a subset of the JavaScript Programming Language. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. JSON structure is built around name:value pairs and ordered list of values. <https://www.json.org> The first function, j_encode(), let you transform a data.frame or list to a 'base64' encoded JSON (or JSON string). The j_decode() function takes a 'base64' string (could be an encoded JSON) and transform it to a data.frame (or list, depending of the JSON structure).
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2024-01-16 |
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r-joiner
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Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues <doi:10.1093/biostatistics/1.4.465> (single event time) and by Williamson and colleagues (2008) <doi:10.1002/sim.3451> (competing risks events time) to a single continuous repeated measure. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-varying covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by a latent Gaussian process. The model is estimated using am Expectation Maximization algorithm. Some plotting functions and the variogram are also included. This project is funded by the Medical Research Council (Grant numbers G0400615 and MR/M013227/1).
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2024-01-16 |
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r-jmv
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A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).
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2024-01-16 |
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r-jrvfinance
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Implements the basic financial analysis functions similar to (but not identical to) what is available in most spreadsheet software. This includes finding the IRR and NPV of regularly spaced cash flows and annuities. Bond pricing and YTM calculations are included. In addition, Black Scholes option pricing and Greeks are also provided.
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2024-01-16 |
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r-jrich
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These functions calculate the taxonomic measures presented in Miranda-Esquivel (2016). The package introduces Jack-knife resampling in evolutionary distinctiveness prioritization analysis, as a way to evaluate the support of the ranking in area prioritization, and the persistence of a given area in a conservation analysis. The algorithm is described in: Miranda-Esquivel, D (2016) <DOI:10.1007/978-3-319-22461-9_11>.
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2024-01-16 |
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r-jrc
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An 'httpuv' based bridge between R and 'JavaScript'. Provides an easy way to exchange commands and data between a web page and a currently running R session.
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2024-01-16 |
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r-jquerylib
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Obtain any major version of 'jQuery' (<https://code.jquery.com/>) and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown'). Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.
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2024-01-16 |
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r-jpen
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A Joint PENalty Estimation of Covariance and Inverse Covariance Matrices.
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2024-01-16 |
