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r-netindices
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Given a network (e.g. a food web), estimates several network indices. These include: Ascendency network indices, Direct and indirect dependencies, Effective measures, Environ network indices, General network indices, Pathway analysis, Network uncertainty indices and constraint efficiencies and the trophic level and omnivory indices of food webs.
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2023-06-16 |
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r-nb
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Estimate the effective population size of a closed population using genetic data collected from two or more data points.
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2023-06-16 |
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r-mvprobit
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Tools for estimating multivariate probit models, calculating conditional and unconditional expectations, and calculating marginal effects on conditional and unconditional expectations.
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2023-06-16 |
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r-multdm
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Allows to perform the multivariate version of the Diebold-Mariano test for equal predictive ability of multiple forecast comparison. Main reference: Mariano, R.S., Preve, D. (2012) <doi:10.1016/j.jeconom.2012.01.014>.
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2023-06-16 |
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r-mulset
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Computes efficient data distributions from highly inconsistent datasets with many missing values using multi-set intersections. Based upon hash functions, 'mulset' can quickly identify intersections from very large matrices of input vectors across columns and rows and thus provides scalable solution for dealing with missing values. Tomic et al. (2019) <doi:10.1101/545186>.
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2023-06-16 |
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r-mstrio
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Interface for creating data sets and extracting data through the 'MicroStrategy' REST API. Access the demo API at <https://demo.microstrategy.com/MicroStrategyLibrary/api-docs/index.html>.
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2023-06-16 |
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r-msaface
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The new methodology "moving subset analysis" provides functions to investigate the effect of environmental conditions on the CO2 fertilization effect within longterm free air carbon enrichment (FACE) experiments. In general, the functionality is applicable to derive the influence of a third variable (forcing experiment-support variable) on the relation between a dependent and an independent variable.
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2023-06-16 |
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r-modmarg
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Calculate predicted levels and marginal effects, using the delta method to calculate standard errors. This is an R-based version of the 'margins' command from Stata.
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2023-06-16 |
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r-mle.tools
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public |
Calculates the expected/observed Fisher information and the bias-corrected maximum likelihood estimate(s) via Cox-Snell Methodology.
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2023-06-16 |
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r-mkin
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Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers and a choice of the optimisation methods made available by the 'FME' package. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using compiled C functions. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
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2023-06-16 |
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r-migration.indices
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This package provides various indices, like Crude Migration Rate, different Gini indices or the Coefficient of Variation among others, to show the (un)equality of migration.
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2023-06-16 |
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r-micropop
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Modelling interacting microbial populations - example applications include human gut microbiota, rumen microbiota and phytoplankton. Solves a system of ordinary differential equations to simulate microbial growth and resource uptake over time.
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2023-06-16 |
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r-micompr
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A procedure for comparing multivariate samples associated with different groups. It uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. The procedure is independent of the distributional properties of samples and automatically selects features that best explain their differences, avoiding manual selection of specific points or summary statistics. It is appropriate for comparing samples of time series, images, spectrometric measures or similar multivariate observations.
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2023-06-16 |
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r-mi
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The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.
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2023-06-16 |
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r-mederrrank
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Two distinct but related statistical approaches to the problem of identifying the combinations of medication error characteristics that are more likely to result in harm are implemented in this package: 1) a Bayesian hierarchical model with optimal Bayesian ranking on the log odds of harm, and 2) an empirical Bayes model that estimates the ratio of the observed count of harm to the count that would be expected if error characteristics and harm were independent. In addition, for the Bayesian hierarchical model, the package provides functions to assess the sensitivity of results to different specifications of the random effects distributions.
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2023-06-16 |
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r-maxlike
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Provides a likelihood-based approach to modeling species distributions using presence-only data. In contrast to the popular software program MAXENT, this approach yields estimates of the probability of occurrence, which is a natural descriptor of a species' distribution.
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2023-06-16 |
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r-maples
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MAPLES is a general method for the estimation of age profiles that uses standard micro-level demographic survey data. The aim is to estimate smoothed age profiles and relative risks for time-fixed and time-varying covariates.
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2023-06-16 |
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r-mac
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This is an integrated meta-analysis package for conducting a correlational research synthesis. One of the unique features of this package is in its integration of user-friendly functions to facilitate statistical analyses at each stage in a meta-analysis with correlations. It uses recommended procedures as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).
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2023-06-16 |
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r-ltsbase
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This is a new tool to estimate Ridge and Liu estimators based on LTS method in multiple linear regression analysis.
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2023-06-16 |
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r-lspline
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Linear splines with convenient parametrisations such that (1) coefficients are slopes of consecutive segments or (2) coefficients are slope changes at consecutive knots. Knots can be set manually or at break points of equal-frequency or equal-width intervals covering the range of 'x'. The implementation follows Greene (2003), chapter 7.2.5.
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2023-06-16 |
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r-lpwc
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Computes a time series distance measure for clustering based on weighted correlation and introduction of lags. The lags capture delayed responses in a time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter (2018) <doi:10.1101/292615>.
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2023-06-16 |
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r-logistic4p
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Error in a binary dependent variable, also known as misclassification, has not drawn much attention in psychology. Ignoring misclassification in logistic regression can result in misleading parameter estimates and statistical inference. This package conducts logistic regression analysis with misspecification in outcome variables.
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2023-06-16 |
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r-lock5withr
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Data sets and other utilities for 'Statistics: Unlocking the Power of Data' by Lock, Lock, Lock, Lock and Lock (ISBN : 978-0-470-60187-7, http://lock5stat.com/).
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2023-06-16 |
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r-localcontrolstrategy
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Especially when cross-sectional data are observational, effects of treatment selection bias and confounding are revealed by using the Nonparametric and Unsupervised "preprocessing" methods central to Local Control (LC) Strategy. The LC objective is to estimate the "effect-size distribution" that best quantifies a potentially causal relationship between a numeric y-Outcome variable and a t-Treatment variable. This t-variable may be either binary {1 = "new" vs 0 = "control"} or a numeric measure of Exposure level. LC Strategy starts by CLUSTERING experimental units (patients) on their pre-exposure X-Covariates, forming mutually exclusive and exhaustive BLOCKS of relatively well-matched units. The implicit statistical model for LC is thus simple one-way ANOVA. The Within-Block measures of effect-size are Local Rank Correlations (LRCs) when Exposure is numeric with more than two levels. Otherwise, Treatment choice is Nested within BLOCKS, and effect-sizes are LOCAL Treatment Differences (LTDs) between within-cluster y-Outcome Means ["new" minus "control"]. An Instrumental Variable (IV) method is also provided so that Local Average y-Outcomes (LAOs) within BLOCKS may also contribute information for effect-size inferences ...assuming that X-Covariates influence only Treatment choice or Exposure level and otherwise have no direct effects on y-Outcome. Finally, a "Most-Like-Me" function provides histograms of effect-size distributions to aid Doctor-Patient communications about Personalized Medicine.
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2023-06-16 |
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r-listwithdefaults
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Provides a function that, as an alternative to base::list, allows default values to be inherited from another list.
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2023-06-16 |
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r-lestat
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Some simple objects and functions to do statistics using linear models and a Bayesian framework.
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2023-06-16 |
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r-leersiecyl
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Functions to download data from the SIE, which is the Statistical Information System (Sistema de Información Estadística) in the Statistical Portal of the Government of Castilla y León (Spain) <https://estadistica.jcyl.es>.
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2023-06-16 |
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r-ldtests
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Exact tests for Linkage Disequilibrium (LD) and Hardy-Weinberg Equilibrium (HWE). - 2-sided LD tests based on different measures of LD (Kulinskaya and Lewin 2008) - 1-sided Fisher's exact test for LD - 2-sided Haldane test for HWE (Wiggington 2005) - 1-sided test for inbreeding - conditional p-values proposed in Kulinskaya (2008) to overcome the problems of asymetric distributions (for both LD and HWE)
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2023-06-16 |
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r-lcfdata
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This package contains (1) event-related brain potential data recorded from 10 participants at electrodes Fz, Cz, Pz, and Oz (0--300 ms) in the context of Antoine Tremblay's PhD thesis (Tremblay, 2009); (2) ERP amplitudes at electrode Fz restricted to the 100 to 175 millisecond time window; and (3) plotting data generated from a linear mixed-effects model.
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2023-06-16 |
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r-ldcorsv
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Four measures of linkage disequilibrium are provided: the usual r^2 measure, the r^2_S measure (r^2 corrected by the structure sample), the r^2_V (r^2 corrected by the relatedness of genotyped individuals), the r^2_VS measure (r^2 corrected by both the relatedness of genotyped individuals and the structure of the sample).
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2023-06-16 |
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r-lcyanalysis
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Analysis of stock data ups and downs trend, the stock technical analysis indicators function have trend line, reversal pattern and market trend.
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2023-06-16 |
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r-lcf
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Baseline correction, normalization and linear combination fitting (LCF) of X-ray absorption near edge structure (XANES) spectra. The package includes data loading of .xmu files exported from 'ATHENA' (Ravel and Newville, 2005) <doi:10.1107/S0909049505012719>. Loaded spectra can be background corrected and all standards can be fitted at once. Two linear combination fitting functions can be used: (1) fit_athena(): Simply fitting combinations of standards as in ATHENA, (2) fit_float(): Fitting all standards with changing baseline correction and edge-step normalization parameters.
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2023-06-16 |
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r-leabra
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The algorithm Leabra (local error driven and associative biologically realistic algorithm) allows for the construction of artificial neural networks that are biologically realistic and balance supervised and unsupervised learning within a single framework. This package is based on the 'MATLAB' version by Sergio Verduzco-Flores, which in turn was based on the description of the algorithm by Randall O'Reilly (1996) <ftp://grey.colorado.edu/pub/oreilly/thesis/oreilly_thesis.all.pdf>. For more general (not 'R' specific) information on the algorithm Leabra see <https://grey.colorado.edu/emergent/index.php/Leabra>.
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2023-06-16 |
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r-lagged
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Provides classes and methods for lagged objects.
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2023-06-16 |
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r-kstatistics
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Methods and tools for estimate (joint) cumulants of a given population distribution using (multivariate) k-statistics and (multivariate) polykays,symmetric unbiased estimators with minimum variance. For more details see Di Nardo E., Guarino G., Senato D. (2009) <arXiv:0807.5008>.
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2023-06-16 |
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r-ksd
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An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <http://arxiv.org/abs/1602.03253>.
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2023-06-16 |
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r-kpeaks
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The input argument k which is the number of clusters is needed to start all of the partitioning clustering algorithms. In unsupervised learning applications, an optimal value of this argument is widely determined by using the internal validity indexes. Since these indexes suggest a k value which is computed on the clustering results after several runs of a clustering algorithm they are computationally expensive. On the contrary, 'kpeaks' enables to estimate k before running any clustering algorithm. It is based on a simple novel technique using the descriptive statistics of peak counts of the features in a data set.
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2023-06-16 |
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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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2023-06-16 |
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r-junr
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The 'Junar' API is a commercial platform to organize and publish data <http://www.junar.com>. It has been used in a number of national and local government Open Data initiatives in Latin America and the USA. This package is a wrapper to make it easier to access data made public through the 'Junar' API.
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2023-06-16 |
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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.
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2023-06-16 |
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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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2023-06-16 |
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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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2023-06-16 |
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r-jose
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Read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are the basis for services like OAuth 2.0 or LetsEncrypt and are natively supported by browsers via the JavaScript WebCryptoAPI.
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2023-06-16 |
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r-jointpm
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A bivariate integration method to estimate risk caused by two extreme and dependent forcing variables.
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2023-06-16 |
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r-jmuoutlier
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Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.
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2023-06-16 |
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r-jmisc
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Some handy function in R
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2023-06-16 |
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r-jlctree
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Implements the tree-based approach to joint modeling of time-to-event and longitudinal data. This approach looks for a tree-based partitioning such that within each estimated latent class defined by a terminal node, the time-to-event and longitudinal responses display a lack of association. See Zhang and Simonoff (2018) <arXiv:1812.01774>.
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2023-06-16 |
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r-istacr
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You can access to open data published in Instituto Canario De Estadistica (ISTAC) APIs at <https://www.gobiernodecanarias.org/istac/api/>.
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2023-06-16 |
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r-isoweek
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This is an substitute for the %V and %u formats which are not implemented on Windows. In addition, the package offers functions to convert from standard calender format yyyy-mm-dd to and from ISO 8601 week format yyyy-Www-d.
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2023-06-16 |
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r-ism
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The development of ISM was made by Warfield in 1974. ISM is the process of collaborating distinct or related essentials into a simplified and an organized format. Hence, ISM is a methodology that seeks the interrelationships among the various elements considered and endows with a hierarchical and multilevel structure. To run this package user needs to provide a matrix (VAXO) converted into 0's and 1's. Warfield,J.N. (1974) <doi:10.1109/TSMC.1974.5408524> Warfield,J.N. (1974, E-ISSN:2168-2909).
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2023-06-16 |
