This package provides a function for reconstructing DNA methylation values from raw measurements. It iteratively implements the group fused lars to smooth related-by-location methylation values and the constrained least squares to remove probe affinity effect across multiple sequences.

netSmooth is an R package for network smoothing of single cell RNA sequencing data. Using bio networks such as protein-protein interactions as priors for gene co-expression, netsmooth improves cell type identification from noisy, sparse scRNAseq data.

This package provides non-invasive annotation of package load calls such as \codelibrary(), \codep_load(), and \coderequire() so that we can have an idea of what the packages we are loading are meant for.

Developed as an R alternative to the AeroEvap model developed by the Desert Research Institute (DRI) in python <https://github.com/WSWUP/AeroEvap/blob/master/README.rst> which estimates open water evaporation using the aerodynamic mass transfer approach.

Fits multivariate models in an R-vine pair copula construction framework, in such a way that the conditional copula can be easily evaluated. In addition, the package implements functionality to compute or approximate the conditional expectation via the conditional copula.

Estimation and inference methods for the continuous threshold expectile regression. It can fit the continuous threshold expectile regression and test the existence of change point, for the paper, "Feipeng Zhang and Qunhua Li (2016). A continuous threshold expectile regression, submitted.".

Produce an averaging estimate/prediction by combining all candidate models for partial linear functional additive models, using multi-fold cross-validation criterion. More details can be referred to arXiv e-Prints via <doi:10.48550/arXiv.2105.00966>.

This package provides a framework for creating production outputs. Users can frame a table, listing, or figure with headers and footers and save to an output file. Stores an intermediate docorator object for reproducibility and rendering to multiple output types.

This package provides a Graphical User Interface (GUI) to import, save, detrend and perform standard tree-ring analyses. The interactive detrending allows the user to check how well the detrending curve fits each time-series and change it when needed.

DECORATE (Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples) builds an ensemble of J48 trees by recursively adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005) <DOI:10.1016/j.inffus.2004.04.001>").

This package creates graphs of species associations (interactions) and ordination biplots from co-occurrence data by fitting discrete gaussian copula graphical models. Methods described in Popovic, GC., Hui, FKC., Warton, DI., (2018) <doi:10.1016/j.jmva.2017.12.002>.

This package contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.

This package provides analytics directly from R'. It requires: FormShare App': <https://github.com/qlands/FormShare >= 2.22.0> . Analytics plugin: <https://github.com/qlands/formshare_analytics_plugin> . Remote SQL plugin: <https://github.com/qlands/formshare_sql_plugin> .

An interface to the fastText library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use fastTextR can be found in the README file.

This package provides a wide variety of tools for general data analysis, wrangling, spelling, statistics, visualizations, package development, and more. All functions have vectorized implementations whenever possible. Exported names are designed to be readable, with longer names possessing short aliases.

The free group in R; juxtaposition is represented by a plus. Includes inversion, multiplication by a scalar, group-theoretic power operation, and Tietze forms. To cite the package in publications please use Hankin (2022) <doi:10.48550/ARXIV.2212.05883>.

This package provides a collection difference measures for multivariate Gaussian probability density functions, such as the Euclidea mean, the Mahalanobis distance, the Kullback-Leibler divergence, the J-Coefficient, the Minkowski L2-distance, the Chi-square divergence and the Hellinger Coefficient.

This is an add on package to GAMLSS. The purpose of this package is to allow users to defined truncated distributions in GAMLSS models. The main function gen.trun() generates truncated version of an existing GAMLSS family distribution.

Interaction and analysis of multiple response data, along with other tools for analysing these types of data including missing value analysis and calculation of standard errors for a range of covariance matrix results (proportions, multinomial, independent samples, and multiple response).

Robust test(s) for model diagnostics in regression. The current version contains a robust test for functional specification (linearity). The test is based on the robust bounded-influence test by Heritier and Ronchetti (1994) <doi:10.1080/01621459.1994.10476822>.

Handy helper package for cross-referencing lake identifiers among different data sets in the Midwestern United States. There are multiple different state, regional, and federal agencies that have different identifiers on lakes. This package helps you to go between them.

Analyze multilevel networks as described in Lazega et al (2008) <doi:10.1016/j.socnet.2008.02.001> and in Lazega and Snijders (2016, ISBN:978-3-319-24520-1). The package was developed essentially as an extension to igraph'.

Palettes Inspired by Works at the Metropolitan Museum of Art in New York. Currently contains over 50 color schemes and checks for colorblind-friendliness of palettes. Colorblind accessibility checked using the colorblindcheck package by Jakub Nowosad'<https://jakubnowosad.com/colorblindcheck/>.

This package provides functions to enhance the available statistical analysis procedures in R by providing simple functions to analysis and visualize the 16S rRNA data.Here we present a tutorial with minimum working examples to demonstrate usage and dependencies.