Multiply robust estimation for population mean (Han and Wang 2013) <doi:10.1093/biomet/ass087>, regression analysis (Han 2014) <doi:10.1080/01621459.2014.880058> (Han 2016) <doi:10.1111/sjos.12177> and quantile regression (Han et al. 2019) <doi:10.1111/rssb.12309>.

Mustache is a framework-agnostic way to render logic-free views. Think of Mustache as a replacement for your views. Instead of views consisting of ERB or HAML with random helpers and arbitrary logic, your views are broken into two parts: a Ruby class and an HTML template.

Uses multiple AUCs to select a combination of predictors when the outcome has multiple (ordered) levels and the focus is discriminating one particular level from the others. This method is most naturally applied to settings where the outcome has three levels. (Meisner, A, Parikh, CR, and Kerr, KF (2017) <http://biostats.bepress.com/uwbiostat/paper423/>.).

It performs variable selection in a multivariate linear model by estimating the covariance matrix of the residuals then use it to remove the dependence that may exist among the responses and eventually performs variable selection by using the Lasso criterion. The method is described in the paper Perrot-Dockès et al. (2017) <arXiv:1704.00076>.

This package is for designing Crispr/Cas9 and Prime Editing experiments. It contains functions to (1) define and transform genomic targets, (2) find spacers (4) count offtarget (mis)matches, and (5) compute Doench2016/2014 targeting efficiency. Care has been taken for multicrispr to scale well towards large target sets, enabling the design of large Crispr/Cas9 libraries.

Helm sources for searching emails and contacts using mu and mu4e. Mu is an indexer for maildirs and mu4e is a mutt-like MUA for Emacs build on top of mu. Mu is highly efficient making it possible to get instant results even for huge maildirs. It also provides search operators, e.g: from:Peter to:Anne flag:attach search term.

GDB is the GNU debugger. With it, you can monitor what a program is doing while it runs or what it was doing just before a crash. It allows you to specify the runtime conditions, to define breakpoints, and to change how the program is running to try to fix bugs. It can be used to debug programs written in C, C++, Ada, Objective-C, Pascal and more.

The provided package implements multiple contrast tests for functional data (Munko et al., 2023, <arXiv:2306.15259>). These procedures enable us to evaluate the overall hypothesis regarding equality, as well as specific hypotheses defined by contrasts. In particular, we can perform post hoc tests to examine particular comparisons of interest. Different experimental designs are supported, e.g., one-way and multi-way analysis of variance for functional data.

This package provides a latent variable model based on factor analytic and mixture of experts models, designed to infer food intake from multiple biomarkers data. The model is framed within a Bayesian hierarchical framework, which provides flexibility to adapt to different biomarker distributions and facilitates inference on food intake from biomarker data alone, along with the associated uncertainty. Details are in D'Angelo, et al. (2020) <arXiv:2006.02995>.

Code to support a systems biology research program from inception through publication. The methods focus on dimension reduction approaches to detect patterns in complex, multivariate experimental data and places an emphasis on informative visualizations. The goal for this project is to create a package that will evolve over time, thereby remaining relevant and reflective of current methods and techniques. As a result, we encourage suggested additions to the package, both methodological and graphical.

Evaluate hypotheses concerning the distribution of multinomial proportions using bridge sampling. The bridge sampling routine is able to compute Bayes factors for hypotheses that entail inequality constraints, equality constraints, free parameters, and mixtures of all three. These hypotheses are tested against the encompassing hypothesis, that all parameters vary freely or against the null hypothesis that all category proportions are equal. For more information see Sarafoglou et al. (2020) <doi:10.31234/osf.io/bux7p>.

Several multivariate techniques from a biplot perspective. It is the translation (with many improvements) into R of the previous package developed in Matlab'. The package contains some of the main developments of my team during the last 30 years together with some more standard techniques. Package includes: Classical Biplots, HJ-Biplot, Canonical Biplots, MANOVA Biplots, Correspondence Analysis, Canonical Correspondence Analysis, Canonical STATIS-ACT, Logistic Biplots for binary and ordinal data, Multidimensional Unfolding, External Biplots for Principal Coordinates Analysis or Multidimensional Scaling, among many others. References can be found in the help of each procedure.

This package implements analytical methods for multidimensional plant traits, including Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. Provides functions for data analysis, visualization, and network metrics calculation. Methods are based on Grime (1974) <doi:10.1038/250026a0>, Pierce et al. (2017) <doi:10.1111/1365-2435.12882>, Westoby (1998) <doi:10.1023/A:1004327224729>, Yang et al. (2022) <doi:10.1016/j.foreco.2022.120540>, Winemiller et al. (2015) <doi:10.1111/ele.12462>, He et al. (2020) <doi:10.1016/j.tree.2020.06.003>.

Two method new of multigroup and simulation of data. The first technique called multigroup PCA (mgPCA) this multivariate exploration approach that has the idea of considering the structure of groups and / or different types of variables. On the other hand, the second multivariate technique called Multigroup Dimensionality Reduction (MDR) it is another multivariate exploration method that is based on projections. In addition, a method called Single Dimension Exploration (SDE) was incorporated for to analyze the exploration of the data. It could help us in a better way to observe the behavior of the multigroup data with certain variables of interest.

qr_mumps is a software package for the solution of sparse, linear systems on multicore computers based on the QR factorization of the input matrix. Therefore, it is suited to solving sparse least-squares problems and to computing the minimum-norm solution of sparse, underdetermined problems. It can obviously be used for solving square problems in which case the stability provided by the use of orthogonal transformations comes at the cost of a higher operation count with respect to solvers based on, e.g., the LU factorization. qr_mumps supports real and complex, single or double precision arithmetic. This is an experimental version of the package for distributed memory.

This package contains the Mus.musculus object to access data from several related annotation packages.

Xorg mutt-misc fonts.

Documentation at https://melpa.org/#/mustache

Documentation at https://melpa.org/#/term+mux

This package provides install functions of other languages such as java', python'.

Platform Design Info for The Manufacturer's Name Mu11KsubB.

Platform Design Info for The Manufacturer's Name Mu11KsubA.

MultiXml provides swappable XML backends utilizing either LibXML, Nokogiri, Ox, or REXML.

This package provides a package containing an environment representing the Mu11KsubB.CDF file.