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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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2025-04-22 |
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r-migest
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Indirect methods for estimating bilateral migration flows in the presence of partial or missing data, including the estimation of bilateral migration flows from changes in bilateral migrant stock tables (e.g. Abel (2013) <doi:10.4054/DemRes.2013.28.18>).
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2025-04-22 |
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r-midn
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Implementation of the mid-n algorithms presented in Wellek S (2015) <DOI:10.1111/stan.12063> Statistica Neerlandica 69, 358-373 for exact sample size calculation for superiority trials with binary outcome.
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2025-04-22 |
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r-midastouch
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Contains the function mice.impute.midastouch(). Technically this function is to be run from within the 'mice' package (van Buuren et al. 2011), type ??mice. It substitutes the method 'pmm' within mice by 'midastouch'. The authors have shown that 'midastouch' is superior to default 'pmm'. Many ideas are based on Siddique / Belin 2008's MIDAS.
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2025-04-22 |
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r-midas
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Contains functions for converting existing HTML/JavaScript source into equivalent 'shiny' functions. Bootstraps the process of making new 'shiny' functions by allowing us to turn HTML snippets directly into R functions.
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2025-04-22 |
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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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2025-04-22 |
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r-micromapst
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Provides the users with the ability to quickly create Linked Micromap plots for a collection of geographic areas. Linked Micromaps are visualizations of georeferenced data that link statistical graphics to an organized series of small maps or graphic images. The Help description contains examples of how to use the micromapST function. Contained in this package are border group datasets to support creating micromaps for the 50 U.S. states and District of Columbia (51 areas), the U. S. 20 Seer Registries, the 105 counties in the state of Kansas, the 62 counties of New York, the 24 counties of Maryland, the 29 counties of Utah, the 32 administrative areas in China, the 218 administrative areas in the UK and Ireland (for testing only), the 25 districts in the city of Seoul South Korea, and the 52 counties on the Africa continent. A border group dataset contains the boundaries related to the data level areas, a second layer boundaries, a top or third layer boundary, a parameter list of run options, and a cross indexing table between area names, abbreviations, numeric identification and alias matching strings for the specific geographic area. By specifying a border group, the package create micromaps for any geographic region. The user can create and provide their own border group dataset for any area beyond the areas contained within the package. Copyrighted 2013, 2014, 2015 and 2016 by Carr, Pearson and Pickle.
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2025-04-22 |
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r-micromacromultilevel
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Most multilevel methodologies can only model macro-micro multilevel situations in an unbiased way, wherein group-level predictors (e.g., city temperature) are used to predict an individual-level outcome variable (e.g., citizen personality). In contrast, this R package enables researchers to model micro-macro situations, wherein individual-level (micro) predictors (and other group-level predictors) are used to predict a group-level (macro) outcome variable in an unbiased way.
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2025-04-22 |
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r-microbats
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A nature-inspired metaheuristic algorithm based on the echolocation behavior of microbats that uses frequency tuning to optimize problems in both continuous and discrete dimensions. This R package makes it easy to implement the standard bat algorithm on any user-supplied function. The algorithm was first developed by Xin-She Yang in 2010 (<DOI:10.1007/978-3-642-12538-6_6>, <DOI:10.1109/CINTI.2014.7028669>).
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2025-04-22 |
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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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2025-04-22 |
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r-michelrodange
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Michel Rodange was a Luxembourguish writer and poet who lived in the 19th century. His most notable work is Rodange (1872, ISBN:1166177424), ("Renert oder de Fuuß am Frack an a Ma'nsgrëßt"), but he also wrote many more works, including Rodange, Tockert (1928) <https://www.autorenlexikon.lu/page/document/361/3614/1/FRE/index.html> ("D'Léierchen - Dem Léiweckerche säi Lidd") and Rodange, Welter (1929) <https://www.autorenlexikon.lu/page/document/361/3615/1/FRE/index.html> ("Dem Grow Sigfrid seng Goldkuommer"). This package contains three datasets, each made from the plain text versions of his works available on <https://data.public.lu/fr/datasets/the-works-in-luxembourguish-of-michel-rodange/>.
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2025-04-22 |
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r-miceconindex
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Tools for calculating Laspeyres, Paasche, and Fisher price and quantity indices.
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2025-04-22 |
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r-micar
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'Mica' is a server application used to create data web portals for large-scale epidemiological studies or multiple-study consortia. 'Mica' helps studies to provide scientifically robust data visibility and web presence without significant information technology effort. 'Mica' provides a structured description of consortia, studies, annotated and searchable data dictionaries, and data access request management. This 'Mica' client allows to perform data extraction for reporting purposes.
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2025-04-22 |
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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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2025-04-22 |
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r-mhtrajectoryr
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Spontaneous adverse event reports have a high potential for detecting adverse drug reactions. However, due to their dimension, the analysis of such databases requires statistical methods. We propose to use a logistic regression whose sparsity is viewed as a model selection challenge. Since the model space is huge, a Metropolis-Hastings algorithm carries out the model selection by maximizing the BIC criterion.
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2025-04-22 |
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r-mhtdiscrete
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A comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling FWER/FDR for discrete data. Given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha and make decisions. For users' convenience, the functions also provide the output option for printing decision rules.
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2025-04-22 |
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r-mhg
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Runs a minimum-hypergeometric (mHG) test as described in: Eden, E. (2007). Discovering Motifs in Ranked Lists of DNA Sequences. Haifa.
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2025-04-22 |
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r-mhctools
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Ten tools for analysis of major histocompatibility complex (MHC) data in non- model species. The functions are tailored for amplicon data sets that have been filtered using the 'dada2' method (for more information visit <https://benjjneb.github.io/dada2>), but even other data sets can be analyzed, if the data tables are formatted according to the description in each function. The ReplMatch() function matches replicates in data sets in order to evaluate genotyping success. The GetReplTable() and GetReplStats() functions perform such an evaluation. The HpltFind() function infers putative haplotypes from families in the data set. The GetHpltTable() and GetHpltStats() functions evaluate the accuracy of the haplotype inference. The PapaDiv() function compares parent pairs in the data set and calculate their joint MHC diversity, taking into account sequence variants that occur in both parents. The CalcPdist() function calculates the p-distances from pairwise comparisons of all sequences in a data set, and mean p-distances of all pairwise comparisons within each sample in a data set. The function includes the options to specify which codons to compare and to calculate amino acid p-distances. The CreateFas() function creates a fasta file with all the sequences in the data set. The CreateSamplesFas() function creates a fasta file for each sample in the data set.
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2025-04-22 |
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r-mhadaptive
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Performs general Metropolis-Hastings Markov Chain Monte Carlo sampling of a user defined function which returns the un-normalized value (likelihood times prior) of a Bayesian model. The proposal variance-covariance structure is updated adaptively for efficient mixing when the structure of the target distribution is unknown. The package also provides some functions for Bayesian inference including Bayesian Credible Intervals (BCI) and Deviance Information Criterion (DIC) calculation.
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2025-04-22 |
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r-mgsub
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Designed to enable simultaneous substitution in strings in a safe fashion. Safe means it does not rely on placeholders (which can cause errors in same length matches).
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2025-04-22 |
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r-mgraster
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Convenience Functions for R Language Access to the v.1 API of the MG-RAST Metagenome Annotation Server, part of the US Department of Energy (DOE) Systems Biology Knowledge Base (KBase).
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2025-04-22 |
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r-mglm
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Provides functions that (1) fit multivariate discrete distributions, (2) generate random numbers from multivariate discrete distributions, and (3) run regression and penalized regression on the multivariate categorical response data. Implemented models include: multinomial logit model, Dirichlet multinomial model, generalized Dirichlet multinomial model, and negative multinomial model. Making the best of the minorization-maximization (MM) algorithm and Newton-Raphson method, we derive and implement stable and efficient algorithms to find the maximum likelihood estimates. On a multi-core machine, multi-threading is supported.
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2025-04-22 |
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r-mft
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Provides statistical tests and algorithms for the detection of change points in time series and point processes - particularly for changes in the mean in time series and for changes in the rate and in the variance in point processes. References - Michael Messer, Marietta Kirchner, Julia Schiemann, Jochen Roeper, Ralph Neininger and Gaby Schneider (2014), A multiple filter test for the detection of rate changes in renewal processes with varying variance <doi:10.1214/14-AOAS782>. Stefan Albert, Michael Messer, Julia Schiemann, Jochen Roeper, Gaby Schneider (2017), Multi-scale detection of variance changes in renewal processes in the presence of rate change points <doi:10.1111/jtsa.12254>. Michael Messer, Kaue M. Costa, Jochen Roeper and Gaby Schneider (2017), Multi-scale detection of rate changes in spike trains with weak dependencies <doi:10.1007/s10827-016-0635-3>. Michael Messer, Stefan Albert and Gaby Schneider (2018), The multiple filter test for change point detection in time series <doi:10.1007/s00184-018-0672-1>. Michael Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+) Peak detection in time series.
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2025-04-22 |
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r-mfp
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Fractional polynomials are used to represent curvature in regression models. A key reference is Royston and Altman, 1994.
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2025-04-22 |
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r-mfilter
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The mFilter package implements several time series filters useful for smoothing and extracting trend and cyclical components of a time series. The routines are commonly used in economics and finance, however they should also be interest to other areas. Currently, Christiano-Fitzgerald, Baxter-King, Hodrick-Prescott, Butterworth, and trigonometric regression filters are included in the package.
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2025-04-22 |
