Use leaf physiognomic methods to reconstruct mean annual temperature (MAT), mean annual precipitation (MAP), and leaf dry mass per area (Ma), along with other useful quantitative leaf traits. Methods in this package described in Lowe et al. (in review).

Fits generalized linear models where the parameters are subject to linear constraints. The model is specified by giving a symbolic description of the linear predictor, a description of the error distribution, and a matrix of constraints on the parameters.

Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.

Hypergeometric Intersection distributions are a broad group of distributions that describe the probability of picking intersections when drawing independently from two (or more) urns containing variable numbers of balls belonging to the same n categories. <arXiv:1305.0717>.

Reads the output of the PerkinElmer InForm software <http://www.perkinelmer.com/product/inform-cell-analysis-one-seat-cls135781>. In addition to cell-density count, it can derive statistics of intercellular spatial distance for each cell-type.

Fit joint mean-covariance models for longitudinal data. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the Armadillo C++ library for numerical linear algebra and RcppArmadillo glue.

This package provides methods for controlling the median of the false discovery proportion (mFDP). Depending on the method, simultaneous or non-simultaneous inference is provided. The methods take a vector of p-values or test statistics as input.

This package provides a mixed collection of useful and semi-useful diverse statistical functions, some of which may even be referenced in The R Primer book. See Ekstrøm, C. T. (2016). The R Primer. 2nd edition. Chapman & Hall.

Multi-omic (or any multi-view) spectral clustering methods often assume the same number of clusters across all datasets. We supply methods for multi-omic spectral clustering when the number of distinct clusters differs among the omics profiles (views).

Matrix-Based Flexible Project Planning. This package models, plans, and schedules flexible, such as agile, extreme, and hybrid project plans. The package contains project planning, scheduling, and risk assessment functions. Kosztyan (2022) <doi:10.1016/j.softx.2022.100973>.

Calculate POTH for treatment hierarchies from frequentist and Bayesian network meta-analysis. POTH quantifies the certainty in a treatment hierarchy. Subset POTH, POTH residuals, and best k treatments POTH can also be calculated to improve interpretation of treatment hierarchies.

This package provides a non convex optimization package that optimizes any function under the criterion, combination of variables are on the surface of a unit sphere, as described in the paper : Das et al. (2019) <arXiv:1909.04024> .

Simple implementation of Semantic Versioning 2.0.0 ('SemVer') on the vctrs package. This package provides a simple way to create, compare, and manipulate semantic versions in R. It is designed to be lightweight and easy to use.

Implement the algorithm provided in scan for estimating the transmission route on railway network using passenger volume. It is a generalization of the scan statistic approach for railway network to identify the hot railway route for transmitting infectious diseases.

Differentiate client errors (4xx) from server errors (5xx) for the plumber and RestRserve HTTP API frameworks. The package also includes a built-in logging mechanism to standard output (STDOUT) or standard error (STDERR) depending on the log level.

This package provides tools for timescale decomposition of the classic variance ratio of community ecology. Tools are as described in Zhao et al (in prep), extending commonly used methods introduced by Peterson et al (1975) <doi: 10.2307/1936306>.

Recursive partytioning of transformation models with corresponding random forest for conditional transformation models as described in Transformation Forests (Hothorn and Zeileis, 2021, <doi:10.1080/10618600.2021.1872581>) and Top-Down Transformation Choice (Hothorn, 2018, <DOI:10.1177/1471082X17748081>).

An oceanographic data processing package for analyzing and visualizing Video Plankton Recorder data. This package was developed at Bedford Institute of Oceanography'. Functions are designed to process automated image classification output and create organized and easily portable data products.

The zlog package offers functions to transform laboratory measurements into standardised z or z(log)-values. Therefore the lower and upper reference limits are needed. If these are not known they could be estimated from a given sample.

Rspamd is an advanced spam filtering system that allows evaluation of messages by a number of rules including regular expressions, statistical analysis and custom services such as URL black lists. Each message is analysed by Rspamd and given a spam score.

This package provides a Bayesian companion to the rms package, rmsb provides Bayesian model fitting, post-fit estimation, and graphics. It implements Bayesian regression models whose fit objects can be processed by rms functions such as contrast()', summary()', Predict()', nomogram()', and latex()'. The fitting function currently implemented in the package is blrm() for Bayesian logistic binary and ordinal regression with optional clustering, censoring, and departures from the proportional odds assumption using the partial proportional odds model of Peterson and Harrell (1990) <https://www.jstor.org/stable/2347760>.

Retrieves efficiently and reliably Investors Exchange ('IEX') stock and market data using IEX Cloud API'. The platform is offered by Investors Exchange Group (IEX Group). Main goal is to leverage R capabilities including existing packages to effectively provide financial and statistical analysis as well as visualization in support of fact-based decisions. In addition, continuously improve and enhance Riex by applying best practices and being in tune with users feedback and requirements. Please, make sure to review and acknowledge Investors Exchange Group (IEX Group) terms and conditions before using Riex (<https://iexcloud.io/terms/>).

This package provides a classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.

Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions or Exclusion. The main functions of this package are the function APIS_2n(), APIS_3n() and launch_APIShiny(), which perform parentage assignment.