Provides functions to read in and manipulate air quality model output from Models3-formatted files.  This format is used by the Community Multiscale Air Quality (CMAQ) model.

Multi modality data matrices are factorized conjointly into the multiplication of a shared sub-matrix and multiple modality specific sub-matrices, group sparse constraint is applied to the shared sub-matrix to capture the homogeneous and heterogeneous information, respectively. Then the samples are classified by clustering the shared sub-matrix with kmeanspp(), a new version of kmeans() developed here to obtain concordant results. The package also provides the cluster number estimation by rotation cost. Moreover, cluster specific features could be retrieved using hypergeometric tests.

A lightweight, dependency-free data engine for R that provides 
    a grammar for tabular and time-series manipulation. Built entirely on 
    Base R, 'm61r' offers a fluent, chainable API inspired by modern data 
    tools while prioritizing memory efficiency and speed. It includes 
    optimized versions of common data verbs such as filtering, mutation, 
    grouped aggregation, and approximate temporal joins, making it an 
    ideal choice for environments where external dependencies are 
    restricted or where performance in pure R is required.

A computational method developed for model-based analysis of alternative polyadenylation (APA) using 3' end-linked reads. It accurately assigns 3' RNA-seq reads to polyA sites through statistical modeling, and generates multiple statistics for APA analysis. Please also see Li WV, Zheng D, Wang R, Tian B (2021) <doi:10.1186/s13059-021-02429-5>.

Provides an extension of the shadow-test approach to computerized adaptive
    testing (CAT) implemented in the 'TestDesign' package for the assessment framework
    involving multiple tests administered periodically throughout the year. This framework
    is referred to as the Multiple Administrations Adaptive Testing (MAAT) and supports
    multiple item pools vertically scaled and multiple phases (stages) of CAT within each test.
    Between phases and tests, transitioning from one item pool (and associated constraints)
    to another is allowed as deemed necessary to enhance the quality of measurement.